Optical sensor for a wearable device

ABSTRACT

A method, system, or apparatus for determining a hydration condition of a user. The apparatus includes a housing. The apparatus further includes a light source disposed at an edge of the housing in a first position, wherein the light source, when affixed to a surface of a body, is operable to emit light into the body from the first position. The apparatus further includes an optical sensor disposed at the edge of the housing in a second position, the second position being a fixed distance from the first position to measure backscatter of the light reflected by a muscular-walled tube of the body at a depth below the surface of the body.

RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.62/117,282, filed Feb. 17, 2015 and U.S. Provisional Application No.62/192,932, filed Jul. 15, 2015, the entire contents of which areincorporated by reference.

BACKGROUND

Dehydration is a condition in which water in a living body decreasesbelow the individual's normal functioning level. Dehydration oftenoccurs when an individual is exerting energy for extended periods oftime, an individual intakes little or no water, or the temperature risesto a point where an individual cannot excrete enough sweat to maintaintheir normal body temperature. Persons that regularly exert themselvesin low humidity and/or high temperature conditions and/or for extendedperiods of time are prone to experience dehydration or dehydrationsymptoms. Elderly persons and children are also especially prone toexperience dehydration or dehydration symptoms.

When a person experiences a dehydrated condition, the individual'sability to perform tasks may begin to deteriorate. For example, in thecase of long distance endurance athletes, an individual that becomesdehydrated by loss of as little as 2% body weight may begin to havetheir performance impaired. Losses in excess of 5% of body weight candecrease the capacity of an individual to perform a task by as much as30%.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure will be understood more fully from the detaileddescription given below and from the accompanying drawings of variousembodiments of the disclosure. The drawings, however, should not betaken to limit the disclosure to the specific embodiments, but are forexplanation and understanding only.

FIG. 1 depicts an electronic device, according to one embodiment.

FIG. 2A depicts a side view of an electronic device, according to oneembodiment.

FIG. 2B depicts a top and a bottom perspective of an electronic deviceattached to a wrist of an individual, according to one embodiment.

FIG. 3 depicts a top view of the electronic device, according to oneembodiment.

FIG. 4A depicts the underside of an electronic device, according to oneembodiment.

FIG. 4B depicts an underside view or interior view of the electronicdevice, according to one embodiment.

FIG. 5 depicts cross sectional side view of an electronic deviceinteracting with a user, according to one embodiment.

FIG. 6 depicts an electronic device oriented above the radial artery ofa user, according to one embodiment.

FIG. 7 depicts an electronic device having multiple optical sensors andlight sources affixed to a user, according to one embodiment.

FIG. 8 depicts a block diagram of the electronic device, according toone embodiment.

FIG. 9A depicts a flow diagram of a method of determining a hydrationcondition, according to one embodiment.

FIG. 9B illustrates a flow diagram of a method of determining a changein hydration condition of a user, according to one embodiment.

FIG. 10 depicts an electronic device communicating with an externalelectronic device, according to one embodiment.

FIG. 11 depicts an interior view of the electronic device, according toone embodiment.

FIG. 12A depicts an optical sensor and multiple light sources embeddedinto the electronic device, according to one embodiment.

FIG. 12B illustrates a cross sectional view of multiple light sourcesand embedded into an electrical device, according to one embodiment.

FIG. 13 depicts an electronic device in direct communications with acomputing device, according to one embodiment.

FIG. 14 depicts an electronic device and a computing device in indirectcommunication using a communications network, according to oneembodiment.

FIG. 15 depicts body area network (BAN) devices communicating using aBAN, according to one embodiment

FIG. 16 depicts a schematic view of an electronic device, according toone embodiment

FIG. 17 is a block diagram of the electronic device with a correlator, abaseliner, and an alerter, according to one embodiment.

FIG. 18 provides an example illustration of a processing devicedisclosed herein, such as a user equipment (UE), a base station, anelectronic device (UMD), a mobile wireless device, a mobilecommunication device, a tablet, a handset, or other type of wirelessdevice, according to one embodiment.

FIG. 19 a block diagram of an exemplary computer system formed with aprocessor that includes execution units to execute an instruction, whereone or more of the interconnects implement one or more features inaccordance with one example implementation of the present disclosure isillustrated.

DESCRIPTION OF EMBODIMENTS

Contemporary methods of measuring the hydration level of a personinclude measuring body weight changes over a period of time andurinalysis. One crude way of monitoring a person's fluid balance is tomonitor how the body weight of a user changes over a short period oftime. In this method, taking a body weight measurement each morning canshow a pattern of hydration over time. The same method can be applied todetermine how much sweat an athlete excreted while exercising byweighing the athlete before and after exercise.

Urinalysis can also be used to determining moderate changes in aperson's fluid balance. A simple approach to urinalysis is to analyzethe color of the person's urine to determine their hydration level. Morescientific urinalysis tests such as urine specific gravity and urineosmolality can be used for a more accurate measurement of a user's fluidbalance.

However, urinalysis and tracking a user's body weight changes over timeare invasive procedures that fail to give the user real time informationregarding the user's changing hydration condition. Thus, it is desirablethat an individual's hydration level is monitored regularly and anydehydration is detected in the early stage before an individual'sperformance levels are impacted or before they reach a seriousdehydration condition.

The embodiments described herein address the above noted deficiencies bydetermining a hydration condition of a user using spectrophotometry.Spectrophotometry is used to measure how much a compound or substanceabsorbs light by measuring the intensity of a beam of light after thebeam of light passes through a sample of the compound or substance.Light can either be absorbed into a substance or it can be reflected bythe substance. The presence of certain salts, minerals, or compounds ina substance determines which wavelengths are reflected and which areabsorbed. For example, salts, such as potassium and sodium, absorbwavelengths of light at specific frequencies. For example, sodium mayabsorb wavelengths between 535 nanometers (nm) and 735 nanometers. Inanother example, potassium may absorb wavelengths between 680 nanometersand 880 nanometers. Thus, by emitting light with a specific wavelengthcorresponding to a salt, such as sodium or potassium, and measuring theintensity of the light at the specific wavelength after it has passedthrough the salt, it is possible to determine how much of the saltexists in a given sample. In another example, the amount of hemoglobinin the blood stream can be another indicator of the body's hydrationcondition. Hemoglobin absorbs wavelengths of light that areapproximately 660 nanometers, 940 nanometers, and 1320 nanometers.Hemoglobin is the protein molecule in red blood cells that carriesoxygen from the lungs to the body's tissues and returns carbon dioxidefrom the tissues back to the lungs. The wavelengths of light asdiscussed herein are not intended to be limiting. The wavelengths usedfor measurements (such as sodium, potassium, or hemoglobin) may vary orbe within a given range. For example, an electronic device may measurean absorption of hemoglobin at 660 nanometers. In another example, theelectronic device may measure an absorption of hemoglobin at wavelengthsbetween 640 nanometers and 680 nanometers.

In one example, measuring the level of various substances in the humanbody may indicate a hydration condition of the body. Specifically, thelevel of electrolytes in a living body may operate as an indicator tothe hydration condition of the living body. Electrolytes are saltscarrying an electric charge that reside in the blood stream and otherbody fluids. Electrolytes affect the amount of water in the body,acidity of the blood (pH), muscle function, and other importantprocesses. These electrolytes are lost when the body perspires.Specifically, when a person becomes dehydrated, the skin pulls sodiumand to some degree potassium from the blood causing the blood to becomeless concentrated with substances such as sodium and potassium. Two keyelectrolytes, potassium and sodium, help regulate the water balance inthe blood and other bodily tissue. Potassium is a body salt that isimportant to both cellular and electrical functions in the body.Additionally, potassium is one of the main salt in the blood consideredto be an “electrolyte”, along with sodium and chloride. Sodium andpotassium regulates the water balance in the blood stream and otherbodily tissues. Thus, by measuring levels of sodium, potassium and othersubstances in the bloodstream by an electronic device, a hydrationcondition of the body can be determined.

In one embodiment, the electronic device may include a housing shaped tobe worn by a user. The housing can have an outer surface and an innercavity to house electronic components, as discussed in greater detail inthe proceeding paragraphs. In one embodiment, the housing can havemultiple cavities on an outer surface. For example, the housing may havea first cavity, a second cavity, and a third cavity on the underside ofthe outer surface of the housing. In one embodiment, a cavity can be anindentation or a pit an inner surface or outer surface of the housing.In another embodiment, a cavity is a channel that extends from the outersurface of the housing to the inner cavity of the housing. Components ofthe electronic device may be disposed in various channels located in thehousing. For example, a light source may be embedded into a channel ofthe housing, connected to one of the electronic components in the innercavity, and emit light towards a surface of the user's body.

The electronic device may have a first light source disposed into thefirst cavity of the housing, see for example FIG. 5. In one example, thefirst light source may not extent beyond the surface of the housing. Inthis example, the light source may be flush with a first plane definedby a surface of the housing such that both the surface of the housingand the light source contact the skin of the user. In another example,the first light source may be recessed into the housing. In thisexample, the first light source may be recessed into the housing suchthat the first light source does not contact the skin of the user whenthe device is worn by the user. In another example, the first lightsource may extend beyond the surface of the housing for increasedcontact with the skin when the device is worn by the user. The firstlight source may be operable to emit light into the body of the user,where the light includes a first wavelength corresponding to awavelength absorbed by sodium.

In one embodiment, the first light source may emit light of a fullspectrum of wavelengths between 400 nanometers and 1800 nanometers. Inanother example, the first light source may emit light at a discretewavelength corresponding to a wavelength absorbed by a particularsubstance. In another example, the first light source may emit light ofa discrete wavelength at 535 nanometers to correspond to a wavelengthabsorbed by sodium in the body. In another example, the first lightsource may emit light of one or more discrete wavelengths between 535 nmand 735 nm that correspond to the wavelengths absorbed by sodium in thebody. In another example, the first light source may emit light at adiscrete wavelength of 780 nanometers to correspond to a wavelengthabsorbed by potassium in the body. In another example, the first lightsource may emit light of one or more discrete wavelengths between 680nanometers and 880 nanometers that correspond to the wavelengthsabsorbed by potassium in the body.

In one example, the electronic device may measure light of multiplewavelengths to determine a hydration condition of the body. The opticalsensor may take measurements of a full spectrum of measurements over therange of 400 nanometers to 1800 nanometers. These measurements can betaken over a continuous amount of time or periodically. In one example,the electronic device may determine if an amount of light (e.g.,absorption, reflection, or backscatter) at the discrete wavelengths ofthe spectrum of wavelengths have changed over one or more measurements.In this example, the first light source may emit a full spectrum ofwavelengths between 400 nanometers and 1800 nanometers into the body.The electronic device may take continuous measurements over the entirespectrum of wavelengths to determine if an amount of light (e.g.,absorption, reflection, or backscatter) at any discrete waveforms havechanged over multiple measurements. In another embodiment, theelectronic device may take measurements at n number of discretewavelengths out of the spectrum of wavelengths emitted from the firstlight source. In one example, n may be 10. In another example, n may be50 or 100. In another example, harmonically related frequencies may beused to determine a salt content level in the body. For example, ameasurement of light at a wavelength of 645 nanometers may correspond toa measurement of sodium in the body. In some embodiments, a contentlevel of sodium in the body may be determined by measuring an amount oflight at a wavelength that is a multiple of a defined wavelength oflight. For example, the electronic device may measure the sodium in thebody using the optical sensor and a light source that emits light at 645nanometers or 645 nanometers multiplied by n. In this example, when n isequal to 2, the electronic device may measure the sodium in the bodyusing the optical sensor and a light source that emits light at 1290nanometers (645×2 nanometers).

In another embodiment, the electronic device includes a second lightsource disposed into the second cavity of the housing. In one example,the second light source may not extent beyond the surface of thehousing. In another example, the second light source may be recessedinto the housing. In this example, the second light source may berecessed into the housing such that the first light source does notcontact the skin of the user when the device is worn by the user. Inanother example, the second light source may extend beyond the surfaceof the housing for increased contact with the skin when the device isworn by the user. The second light source may be operable to emit lightinto the body of the user, where the second light includes a secondwavelength corresponding to a wavelength absorbed by potassium.

In another embodiment, the electronic device includes an optical sensordisposed into the third cavity of the housing. In one example, theoptical sensor may not extent beyond the surface of the housing. Inanother example, the optical sensor may be recessed into the housing orextend beyond the surface of the housing. In one example, the opticalsensor may be a fixed distance from the first light source, as describedin greater detail in the proceeding paragraphs. In another example, theoptical sensor may be a second fixed distance from the second lightsource, as described in greater detail in the preceding paragraphs. Inanother example, the optical sensor is to detect a portion of the lightreflected by a structure of the body, such as a muscular-walled tube ofthe body, at a depth below the body surface of the user. The precedingexamples are not intended to be limiting. The number of light sources isnot limited the first and second light source. In other embodiments, theelectronic device can include one or a plurality of light sources.Additionally, the number of optical sensors and the distance between theoptical sensors is not intended to be limiting. The electronic devicecan include a one or a plurality of optical sensors at various distancesbetween the optical sensors and the various light sources.

In another embodiment, the electronic device includes a sensor interfacecoupled to the optical sensor. In one example, the sensor interface mayreceive a detected portion of light from the optical sensor and maydetermine a first measurement of backscatter for the first wavelength oflight using the detected portion of the light. In this example, lightreflected by bodily tissue is referred to as backscatter. In anotherexample, the sensor interface may determine a second measurement ofbackscatter for the second wavelength of light using the detectedportion of the light. In one example, backscatter is the diffusedreflection of light due to the scattering of light off bodily tissue. Inanother example, backscatter is the specular reflection, or the directreflection, off bodily. In one embodiment, the sensor interfacedetermines the amount of light which is the diffused reflection of thelight due to the light scattering off a muscular-wall tube of the body.In another embodiment, the sensor interface may determine the amount oflight received by the optical sensor due to the specular reflection ofthe light off a portion of bodily tissue.

In another embodiment, the electronic device may include a processingdevice coupled to the sensor interface. The processing device maycompare the first measurement of backscatter of the first wavelength toa previous measurement of backscatter of the first wavelength anddetermine a change in the sodium level of the body when the amount ofbackscatter of the first wavelength changes. In one example, theprocessing device may compare the second amount of backscatter of thesecond wavelength to a previous measurement of backscatter of the secondwavelength and determine a change in the potassium level of the userwhen the amount of backscatter of the second wavelength changes. Inanother example, the processing device or sensor interface may provide ahydration condition to the user, as described in greater detail in theproceeding paragraphs.

FIG. 1 illustrates an electronic device 110, according to oneembodiment. FIG. 1 illustrates that the electronic device 110 can be awearable device such as a wristband, a headband, an armband, a chestband, a leg band, an ankle band, a strap, a garment or piece of clothing(such as a hardhat or shirt), an accessory, or other object that can beshaped to attach or couple to an user. The electronic device 110 canalso be integrated into other wearable objects such as a hard hat, asafety harness, a safety lock out, shoes, a bag, and so forth.Alternatively, the electronic device may be an implantable device thatmay be implanted under the skin of the user.

In one example, the electronic device 100 can be located in an area thatis practical for the individual to wear the electronic device 110 for anextended period of time, such as a 24-hour period. For example, as manyindividuals are accustom to wearing wristwatches, a comfortable locationfor the individual to wear the electronic device 110 for an extendedperiod of time may be at the wrist location. In another example, theelectronic device may be located at a location on the individual thatwill provide a high measurement accuracy level, such as a location onthe individual that is the most sensitive to a selected physiologicalmeasurement. For example, the chest, wrist, tip of the finger, or earlobe may be locations that are sensitive to taking physiologicalmeasurements and the electronic device 110 can be shaped to attach tothe individual at chest, wrist, tip of the finger, or ear lobelocations.

In one embodiment, the electronic device 110 may include a housing 115with one or more inner cavities. The one or more cavities can includespace to house: a sensor array 120, a sensor 130, a display 140, aprocessing device 150, a memory device 160, a communication device 170,and/or a battery management system (BMS) 180. In one embodiment, thehousing 115 can be hermetically sealed, e.g., airtight, water proof,sweat proof, dust proof, and so forth. In another example, the housingcan be a unibody (e.g., a single unit), where components such as thesensor 130 can be sealed within the unibody. In another embodiment, thehousing 115 can include multiple pieces, such as a first housing pieceand a second housing piece, that are sealed together to form ahermetically sealed housing 115.

In one example, the electronic device 110 can be an invasive deviceattachable to (or implantable within) a body of a user to obtain aninvasive physiological measurements from the user. In another example,the electronic device 110 can be a non-invasive device attachable to thebody of the user to obtain non-invasive measurements from the user.

The electronic device 110 can include a sensor 130 or sensor array 120that can be integrated into the electronic device 110. In anotherexample, the sensor 130 or the sensor array 120 can be coupled to theprocessing device 150 of the hydration monitoring device. 110. In oneexample, the sensor 130 can be a physiological sensor. The physiologicalsensor can include an impedance sensor, an optical sensor, anelectrocardiography (ECG) sensor, a fluid level sensor, an oxygensaturation sensor, a body temperature sensor (skin temperature or coretemperature), a plethysmographic sensor, a respiration sensor, a breathrate sensor, a cardiac sensor, a bio-impedance sensor, a spectrometer, aheart rate sensor, a blood pressure sensor, a pulse oximeter, or otherphysiological sensors. In another example, the sensor 130 can be aNewtonian sensor. The Newtonian sensor can include: a two dimensional(2D) accelerometer, a three dimensional (3D) accelerometer, a gyroscope,a magnetometer, a vibration sensor, a force sensor, a pedometer, astrain gauge, and so forth. In another example, the sensor 130 can be alocation sensor. The location sensor can include: a global positioningsystem (GPS); a triangulation system; and so forth. In another example,the sensor 130 can be an environmental sensor. The environmental sensorcan include: a humidity sensor, an ambient temperature sensor, analtitude sensor, a barometer, a weather sensor, and so forth. In oneembodiment, the sensor 130 can be a non-invasive sensor. In oneembodiment, one or more of the physiological sensors, the Newtoniansensors, or the environmental sensors can be integrated into theelectronic device 110 or physically coupled to the electronic device110. In another example, one or more of the physiological sensors, theNewtonian sensors, or the environmental sensors can be physicallyseparate from the electronic device 110 and can be communicate data withthe electronic device, either directly or indirectly as discussedherein.

In one embodiment, the electronic device 110 can include a display 140to show information to a user or a third party based on the measurementsfrom the sensor 130 or the sensor array 120. In one embodiment, thedisplay 140 can show the time, e.g., a clock. In another embodiment, theinformation shown on the display 140 may include measurementinformation, such as: a light backscatter measurement, a heart rate ofan individual, a breathing rate of the individual, a blood pressure ofthe individual, and so forth. In another example, the information shownon the display 140 may include recommendations, such as: arecommendation to take a break; a recommendation to go home; arecommendation to go to a hospital; or other recommendations. In anotherexample, the information shown on the display 140 may include alerts,such as: an alert that a user may be experiencing a dehydrationcondition; an alert to take medication; an alert that an environment maynot be safe; an alert that the user has fallen down; or other alerts. Inanother example, the information shown on the display 140 may include:hydration information, health status information, and other information.

In another embodiment, the display 140 can display information to a useror a third party based on information from other devices incommunication with the electronic device 110. For example, theelectronic device 110 can receive information from an automobile or asmart home device of a user or a third party. In this example, theinformation from the automobile or the smart home device can includeambient temperatures, humidity information, weather information, and soforth. The electronic device 110 can display the information from theautomobile or the smart home device or use it in combination withmeasurements taken using the sensor 130 or the sensor array 120 todetermine and display other information, such as a hydration level ofthe user.

In another embodiment, the processing logic of the electronic device 110can determine an error with the sensor 130 or the sensor array 120 anddisplay the error to the user or the third party using the display 140.For example, the processing logic can determine that the sensor 130 orthe sensor array 120 is not interfacing with the user properly and theprocessing logic can use the display 140 to display an error message tothe user. In one embodiment, the sensor 130 or the sensor array 120 isnot interfacing with the user properly when the sensor 130 or the sensorarray 120 is only partially contacting the body of the individual or isnot completely contacting the body of the individual. In anotherembodiment, the sensor 130 or the sensor array 120 is not interfacingwith the user properly when an object or particle is interfering withprocessing logic using the sensor 130 or the sensor array 120 to takephysiological measurements of the user, environmental measurements, orother measurements. In one example, processing logic can determine thatobject or particle is interfering with taking measurements whenmeasurement information is outside a defined measurement range or thereis a discontinuity in the measurement information that exceeds athreshold level for the discontinuity. For example, when dirt comesbetween the sensor 130 or the sensor array 120 and the body of the user,the dirt can cause a discontinuity in the measurement information. Whenthe processing logic determines the discontinuity in the measurementinformation, the processing logic can use the display 140 to display anerror message associated with the discontinuity.

In another embodiment, the sensor 130 or the sensor array 120 is notinterfacing with the user properly when the electronic device 110, thesensor 130, or the sensor array 120 has become dislocated or displaced.For example, measurements taken using the sensor 130 or the sensor array120 with a first orientation can have a higher accuracy level thanmeasurements taken using the sensor 130 or the sensor array 120 with asecond orientation. In one example, the first orientation is anorientation where the user is wearing the electronic device 110 in acorrect orientation and the second orientation is an orientation whenthe electronic device 110 has slipped or shifted to a differentorientation. When the electronic device 110 has slipped or shifted thesecond orientation, the processing logic identifies that a measurementis outside a defined measurement range or there is a discontinuity inmeasurement information and uses the display 140 to display an errormessage associated with slippage or shifting.

In one example, the display 140 can be a touch screen display, such as acapacitive touch screen or a resistive touch screen. In another example,the display 140 can display a graphical user interface (GUI) to receiveinformation. In another example, the electronic device 110 can include adata port 165, such as a universal serial bus (USB) port, a mini-USBport, a micro-USB port, a LIGHTNING® port, and so forth. In anotherexample, the electronic device 110 can include a wireless communicationsdevice 170 (as discussed in the proceeding paragraphs) to send orreceive information. The electronic device 110 can include a processoror processing device 150 to analyze or process measurements, receivedinformation, user input data, and/or other types of data.

In one example, the electronic device 110 can monitor stress on arespiratory system of the individual. For example, the electronic device110 can use the sensor 130, such as an oxygen saturation sensor, tomonitor the stress on a respiratory system of the individual.

In another example, the electronic device 110 can use one or moresensors 130 in the sensor array 120 to monitor stress on a plurality ofsystems of an individual, such as a biological system or a body system.The biological system may include a respiratory system, a cardiovascularsystem, a nervous system, an integumentary system, a urinary system, anexcretory system, a digestive system, an immune system, an endocrinesystem, a lymphatic system, a muscular system, a skeletal system, areproductive system, and other systems. The body system may include twoor more organs working together in the execution of a specific bodilyfunction, e.g., a neuroendocrine system, a musculoskeletal system, etc.For example, the electronic device 110 can monitor stress on the cardiacsystem of an individual using a blood pressure sensor of the sensorarray 120 and can monitor the stress on the respiratory system of theindividual using an oxygen saturation sensor of the sensor array 120.

In another example, the electronic device 110 can monitor biologicalsystems, organs, body parts, body system, or other areas of anindividual. In another example, the electronic device 110 can monitor oraggregate stress measurements from the sensors of the sensor array withother measurements, such as a lung capacity of an individual, ahematocrit (HCT), an oxygen saturation level, and/or or other medicalmeasurements. In another example, the electronic device 110 can analyzethe aggregated measurements to determine stress on one or morebiological systems, organs, body parts, and/or body system and use theaggregated measurements to determine medical, health, and/or safetyconditions.

In one example, the electronic device 110 can use the sensor array 120to monitor a medical condition of an individual, such as a cardiaccondition, under various environments or conditions for continuous,semi-continuous, or a periodic period of time on a long-term orprotracted basis. In one example, sensor measurements can be collectedusing the sensor 130 in the sensor array 120 of the electronic device110. In another example, the sensor measurements can be stored on anon-tangible computer readable medium device 160 (e.g., a memory device)coupled to the electronic device 110 or in communication with theelectronic device 110.

In one embodiment, the battery management system (BMS) 180 can include:one or more batteries (such as a rechargeable battery), a charger, and amanagement device. The management device can manage and control power,e.g., power to and from the one or more batteries or regulate power ofthe electronic device 110. For example, the management device can directpower received from an external power source, such as wall outlet, viathe data port 165 (e.g., a USB port) and can recharge the one or morebatteries. In another example, the BMS 180 can include a wireless powersystem with a wireless power coil to receive power. In this example, themanagement device can direct power received via the wireless powersystem to the one or more batteries. In another example, the managementdevice can direct power to components or systems of the electronicdevice 110, such as the sensor array 120, the sensor 130, the display140, the processing device 150, the memory device 160, and/or thecommunication device 170. In one example, the management device can be aprocessor or another processing device, independent of the processingdevice 150, that can manage and control the power. In another example,the management device can be software executed by the processing device150 or processing logic to manage the power.

In one embodiment, the BMS 180 can determine when a charge level the oneor more batteries is below a threshold amount and can send anotification to the user indicating that the electronic device 110 needsto be charged. In one example, the electronic device can send thenotification to the user using a sensory device such as a vibrator, aspeaker, a display, and so forth.

FIG. 2A illustrates a side view of an electronic device 200, accordingto one embodiment. The electronic device 200 can include one or moreintegrated sensors 220. In one exemplary embodiment, the electronicdevice 200 can have a flat top portion 230 and a circular remainingportion 240 to fit to the contour or shape of a wrist on a user. Anadvantage of the electronic device 200 fitting to contours of the wristcan be to align the sensors 220 of the electronic device 200 with aspecific location on the wrist of the individual (such as a bottom,side, or top of the wrist). The electronic device 200 may be fit to thecontours of the wrist to provide and/or maintain proper contact betweenthe sensor 220 of the electronic device 200 and a body of the user. Thelocation of the sensors 220 is not intended to be limiting. The sensor220 can be located at different locations on the electronic device 200.Additionally, a shape of the electronic device 200 is not intended to belimiting. The electronic device 200 can be a variety of differentshapes, such as oval, circular, rectangular, and so forth.

FIG. 2B illustrates a top and a bottom perspective of an electronicdevice 200 attached to a wrist 250 of an individual, according to oneembodiment. The electronic device 200 may be located on the wrist of anindividual and may take one or more measurements at the wrist location.In one example, the electronic device 200 can cover or wrap around thecircumference of the wrist 250 of the individual.

FIG. 3 illustrates a top view of the electronic device 300, according toone embodiment. The electronic device 300 may have a display 310. Thedisplay 310 may provide information to a user such as indicating theuser's hydration condition, temporal information such as the user'shydration condition over time, a time and date, and any informationrelevant to a user's physiological state. In one embodiment, the display310 may be a graphical user interface (GUI) that allows a user tointeract with the device. In another embodiment, the display may belocated on an external device, such as a cellular telephone, a personalcomputer, or other mobile device. The electronic device 300 may furtherinclude a power indicator 320 to indicate a state of the electronicdevice 300. In another embodiment, the electronic device 300 maycomprise one or more sensors such as a humidity and/or temperaturesensor 330. In one embodiment, a humidity sensor may detect the humiditylevel of the user's environment or a sweat rate of a user. A temperaturesensor may detect the temperature of the user's environment or a surfacetemperature of a user.

FIG. 4A illustrates the underside of an electronic device 400 isdepicted, according to one embodiment. The electronic device 400includes a housing 410, an optical sensor 420, light sources 430 and440, an impedance sensor 455 including impedance pads 450 and 460,contact wings 470 and 480, and a humidity and/or temperature sensor 490.The housing 410 of the electronic device 400 may be shaped to affix tothe wrist, head, arm, chest, leg, ankle, ear lobe, fingertip, or othersurface of the body. The housing 410 may have one or more cavities tohouse components of the electronic device 400. In one example,electronic device has a cavity 465 to house the second impedance pad460. As previously discussed, the cavity 465 may be disposed on alocation on an outer surface of the housing 410. In this example, theunderside of the housing 410 can be along a portion of the outer surfaceof the housing 410. In one example, the underside of the housing 410 maybe the surface of the device that contacts the user when worn. In thisexample, the cavity 465 may be a channel extending from the underside ofthe outer surface of the housing 410 to an inner cavity of the housing410. The contact terminal may be disposed in the channel such that thecontact terminal is flush with the plane defined by the outer surface ofthe housing 410 and is coupled to another component of the electronicdevice that is disposed in the inner cavity of the housing 410. In otherexamples, the impedance pad 450, optical sensor 420, humidity and/ortemperature port 490, and light sources 430 and 440 are disposed in thecavity 465 or other similar cavities.

The sensor components such as the optical sensor 420, light sources 430and 440, impedance pads 450, 460, and humidity and/or temperature sensor490 may be embedded into the one or more cavities of the underside ofthe housing 410 of the electronic device 400. In some cases, one or moresensor components may sit flush with a plane defined by an underside ofthe housing 410. When affixed to a user, the sensor components contactthe skin of the user without extending beyond the plane defined by theunderside of the housing 410. Alternatively, the sensor components maybe recessed into the housing 410. In this example, the sensor componentsmay be recessed into the housing 410 such that the sensor components donot contact the skin of the user when the device is worn by the user. Inanother example, the sensor components may extend beyond the surface ofthe housing 410 for increased contact with the skin when the device isworn by the user.

The optical sensor 420 may be embedded into cavity 462 and the lightsources 430 and 440 may be embedding into cavities 464 and 466,respectively. Moreover, optical sensor 420 and light sources 430 and 440may be located between impedance pads 450 and 460. In one embodiment,the light sources 430 and 440 are light emitting diodes (LEDs). Inanother embodiment, the light sources 430 and 440 may be incandescentlight sources, halogen light sources, or the like. Light sources 430 and440 may emit a full spectrum wavelength of light. In this example, afull spectrum wavelength describes the electromagnetic spectrum frominfrared to near-ultraviolet. In another example, the light sources 430and 440 may emit a discrete wavelength of light into a body. A discretewavelength of light may be a range of wavelengths taken from theelectromagnetic spectrum. In one example, a discrete wavelength of lightcan be between 535 nanometers and 735 nanometers. In another example,the discrete wavelength of light can be between 680 nanometers and 880nanometers. Further, the discrete wavelengths may correspond tomeasurements of potassium, sodium, or other substances in the bloodstream or other bodily tissue.

In one embodiment, optical sensor 420 is to detect an intensity of lightat one or more wavelengths reflected by bodily tissue of a user. Theoptical sensor 420 is coupled to a processing device and a sensorinterface. The sensor interface may receive the detected light from theoptical sensor and measure the intensities, or the amount of light,received at a specific wavelength. In one embodiment, the optical sensor420 is used in concert with other components of the electronic device400 to determine a hydration condition of the body of a user. Forexample, the sensor interface unit 806 of the electronic device 400 mayuse the optical sensor 420 to detect the backscatter of a wavelengthcorresponding to a salt in the body. In another example, the sensorinterface unit 806 may, through use of the impedance sensor 455, take animpedance measurement of the body. In one embodiment, the electronicdevice 400 may determine a hydration condition of the body using theimpedance measurement or the backscatter measurement. In anotherembodiment, the electronic device 400 may determine a hydrationcondition of the body using the impedance measurement and thebackscatter measurement in parallel or concurrently.

The sensor interface may determine a backscatter measurement bymeasuring the concentration levels of substances, such as electrolytes,in the body. For example, when the sensor interface unit 806 measures adecrease in backscatter from the baseline or previous backscattermeasurement of the user of a wavelength corresponding to sodium in amuscular walled-tube of the body, the sensor interface may determinethat the user's sodium level in the blood stream is increasing and thehydration condition of a user is declining. In one embodiment, the GUIor display may inform the user that they are becoming dehydrated. In theexemplary embodiment, the measurement is taken from a muscular-walledtube of the body such as a vein, artery, or the like. However, themeasurement can be taken from other bodily tissues as well.

In one embodiment, the electronic device 400 includes impedance sensor455 having impedance pads 450 and 460. Impedance sensor 455 may causeimpedance pad 450 to send an electrical signal into a body. Theimpedance pad 460 may detect at least a portion of the electrical signalin the body. In one embodiment, the impedance sensor 455 can detect achange in the impedance of the body. The change in the impedance of thebody can indicate a change in a hydration condition of the body. Forexample, as a level of the impedance increases, the hydration conditionof body may be an increase in dehydration. In another example, as alevel of the impedance decrease, the hydration condition of body may bean increase in hydration. The impedance sensor 455 may be coupled to aprocessing device and a sensor interface through contact wings 470 and480.

In another embodiment, the electronic device 400 includes a humidityand/or temperature sensor 490. In one example, the humidity and/ortemperature sensor 490 may perform a sweat rate measurement to determinean amount the body is perspiring. In another example, the humidityand/or temperature sensor 490 may perform a surface temperaturemeasurement of the skin. In another embodiment, the electronic device400 may also include a pulse oximeter to measure a user's blood oxygenlevel.

FIG. 4B illustrates a bottom view of the electronic device 400,according to one embodiment. The electronic device 400 may include aprocessing device 425 coupled to the sensors 420, 455, and 490 to takeselected measurements. The processing device 425 may receive measurementinformation from the one or more sensors 420, 455, and 490 and analyzethe measurement information to determine selected information, such as ahydration condition, physiological information, medical information, andso forth. In one example, the selected information can be hydrationcondition information, cardiac information (e.g., blood pressure orheart rate), blood oxygen level information, skin luminosityinformation, or other user information.

The electronic device 400 may also include one or more indicators 435used to alert the user of the electronic device 400 of a hydrationcondition change. The indicator 435 may be on the top or the bottom ofthe electronic device 400 based on a type of the indicator 435. Forexample, the indicator 435 can be a display or light may be on the topof the electronic device 400. In another example, the indicator 435 canbe a vibrator on the bottom of the electronic device 400. In anotherexample, the indicator 435 can be a speaker.

FIG. 5 illustrates a cross sectional side view of an electronic device500 interacting with a user, according to one embodiment. The electronicdevice 500 includes a housing 510 with cavities 515 and 525. Theelectronic device 500 may further include a light source 530 embedded incavity 525. In one example, the light source 530 may emit a fullspectrum of wavelengths between 400 nanometers and 1800 nanometers. Inanother example, the light source 530 is an LED emitting light of adiscrete wavelength corresponding to a wavelength absorbed by aparticular substance. In another example, the LED may emit light of adiscrete wavelength between 535 nanometer and 735 nanometers tocorrespond to the wavelengths absorbed by sodium in the body. In anotherexample, the LED may emit light of a discrete wavelength between 680nanometers and 880 nanometers to correspond to the wavelengths absorbedby potassium in the body.

The electronic device 500 further includes an optical sensor 520. Theoptical sensor 520 may receive backscatter 580A-D that has beenreflected by tissue in the body. The optical sensor may be equipped witha lens 590. The lens 590 may be any shape or thickness, and may focus,narrow, or direct the emitted light. Backscatter may be discrete or fullspectrum waveforms that have been reflected off bodily tissue. In someexamples, when the wavelengths hit body tissue or a substance in thebody, the wavelengths are scattered by the tissue or substance. Thesensor interface unit 806 may measure the amount of light that hasscattered by causing the optical sensor 520 to detect the amount oflight that is scattered off body tissue. The processing device maydetermine the sodium or potassium level by comparing the amount of lightemitted with the amount of light that is received at the optical sensor520. The amount of light received by the optical sensor can be comparedto a previous amount of backscatter to determine if the level of thesubstance in the body is increasing or decreasing.

The optical sensor 520 is separated from light source 530 by a fixeddistance 570. Due to the angle of reflection 575 of light waves enteringthe body, the fixed distance 570 is fixed at a distance that allows theoptical sensor 520 to detect backscatter of light that has beenreflected by a desired depth of body tissue. If, for example, theoptical sensor 520 is separated from the light source 530 by 1millimeter (mm) to 3 mm, the optical sensor 520 may detect backscatterthat has reflected off body tissue close to the surface, such as theepidermis and dermis layers 540, of the skin (e.g shallow backscatter585). As the optical sensor 520 is increasingly separated from lightsource 530, the optical sensor may detect light that has penetrated andbeen reflected off deeper parts of bodily tissue. However, if theoptical sensor 520 is separated from light source 530 by too great of afixed distance, the optical sensor 520 will fail to detect enough lightto take a measurement.

In one embodiment, optical sensor 520 and the light source 530 may beseparated by a fixed distance 570 for measuring waveforms that havereflected off a muscular-walled tube of the body such as an artery 550or vein 560. Veins and arteries of the body contain concentrations ofsubstances such as potassium and sodium that correlate with thehydration condition of a body. When a person becomes dehydrated, theskin pulls potassium and sodium from the blood causing the blood tobecome less concentrated with salts such as sodium and potassium. When aperson has a lower than normal sodium content in the blood stream, itmay be an indicator that the person is becoming dehydrated. In somecases, as a person becomes dehydrated the potassium content in the bloodstream may decrease or stay the same. In one example, the electronicdevice 500 will determine the hydration condition of the user bydetermining potassium to sodium ratio. When a person has a higher thannormal potassium to sodium ratio in the blood stream, it may be anindicator that the person is dehydrated. In one example, the electronicdevice may determine the hydration condition of the user be comparingmeasurements of light at various wavelengths corresponding to more thanone salt or substance in the body. In this example, the hydrationcondition may be determined by looking at ratios of the various mineralsor substances in the body as determined by the electronic device. Thus,by measuring backscatter of wavelengths of light that are absorbed bysodium and potassium, the concentration of these substances in the bloodstream can be determined. In another embodiment, when taking ameasurement at the wrist, it may be desirable to separate the opticalsensor 520 from the light source 530 by between 6 millimeters and 8millimeters to measure the backscatter from vein 550 or artery 560. Inone embodiment, to prevent light that has been emitted from light source530 but that has not entered the body from reaching the optical sensor520 and biasing a measurement, light piping or a barrier may be placedbetween the light source 530 and optical sensor 520.

FIG. 6 illustrates, an electronic device 600 oriented above the radialartery 610 of a user, according to one embodiment. The electronic device600, as depicted, is oriented above the radial artery 610 of a user'sarm to measure physiological data, such as a hydration condition. Theelectronic device may be oriented above the radial artery 610 todetermine a concentration of substances such as potassium and sodium ina user's blood stream through a vein or artery. In one example, theelectronic device is oriented above the radial artery 610 because theradial artery 610 is near the surface of the user's body. Measuring at alocation that is near the surface of the skin minimizes the amount ofbackscatter that the optical sensor 620 detects from light that has beenscattered by structures or substances in the body other than theintended artery or vein. To measure waveforms that have reflected offthe radial artery 610, it may be desirable to position light sources 630and 640 on one side of the radial artery 610 and the optical sensor 620on the other side of the radial artery. This orientation allows theoptical sensor 620 to measure backscatter off the radial artery 610. Forexample, when optical sensor 620 is positioned on one side of the radialartery 610 and light sources 630 and 640 are positioned on the otherside of the radial artery 610, light that is emitted from the lightsources 630 and 640 is scattered off the blood or blood constituents inradial artery 610 and detected by optical sensor 620. However, if theelectronic device was not positioned over an artery or vein, such as theradial artery 610, there would not be a main conduit of blood betweenthe light sources 630 and 640 and the optical sensor 620 for the opticalsensor 620 to measure backscatter from. Moreover, optical sensor 620 andlight sources 630, 640 are spaced at fixed distance 670 such that theoptical sensor 620 detects backscatter that has penetrated bodily deepenough to have reflected off the radial artery 610. The radial artery610 is an example of a muscular-walled tube of the body.

In one embodiment, the electronic device 600 measures the level ofpotassium, sodium, or another substance in the radial artery 610 todetermine a hydration condition of the body. Sodium and potassium,individually or in combination, regulate the water balance in the bloodand tissues of a user. Potassium best absorbs light wavelengths between680 nanometers and 880 nanometers. In one example, optical sensor 620detects light of a wavelength of 780 nanometers that has been reflectedby potassium in the radial artery or other muscular-walled tube of thebody to determine a potassium concentration in the blood stream. Anincreasing in the potassium to sodium ratio in the blood stream mayindicate that the body is becoming dehydrated.

In another embodiment, the electronic device 600 measures the level ofsodium in the body. In one example, excess sodium in the blood streamcan cause an increase in the blood pressure of a user. In anotherexample, a lack of sodium can cause a user to suffer nausea, vomiting,exhaustion, and dizziness. Additionally, sodium, along with potassium,is an electrolyte that when measured can be an indicator as to thehydration condition of the body. In one embodiment, sodium may absorbwavelengths between 535 nanometers and 735 nanometers. In one example,optical sensor 620 may detect light of a wavelength of 620 nanometersthat has been reflected by sodium in the radial artery 610 or othermuscular-walled tube of the body to determine a sodium concentration inthe blood stream.

FIG. 7 illustrates, an electronic device 700 having multiple opticalsensors 720A-E and light sources 730A-E and 740A-E affixed to a user,according to one embodiment. Electronic device 700 may have multiplelight source 730A-E and 740A-E and optical sensor 720A-E configurationsspaced around a wrist band, head band, torso band, or the like. In oneembodiment, having multiple light source 730A-E and 740A-E and opticalsensor 720A-E configurations may improve measurement accuracy if theelectronic device 700 shifts on the body. For example, a user exercisingmay cause the electrical device 700 to shift around on the user's wrist.In this example, each set of optical sensor 720A-E and light sources730A-E and 740A-E may be taking measurements of different locationsaround the wrist. The sensor interface may analyze the data from eachset (e.g. optical sensor 720C and light sources 730C and 740C) todetermine which optical sensor and light source set is over the radialartery 710 at any given time, and utilize that set's measurements todetermine a hydration condition of the user. In one example, eachoptical sensor and light source set is concurrently taking measurements.When a set (e.g. optical sensor 720C and light sources 730C and 740C) isreading measurement data within a specific range known to be within themeasurement range of a user's baseline hydration level or within therange of previous measurement taken from the user's radial artery, thatspecific set is used to determine a hydration condition. Further,optical sensor and light source sets that are detecting measurementsoutside of the user's known range may be presumed to not be measuringfrom the radial artery and these measurements may be discarded. Inanother example, if multiple optical sensor and light source sets arewithin the range known to be within the range of previous measurementstaken from the user's radial artery, each of these measurements will beaggregated and used to determine the hydration condition of the user.

FIG. 8 illustrates a block diagram of the electronic device 800,according to one embodiment. The electronic device 800 may include apower source 802, a processing device 804, a sensor interface unit 806,an analysis unit 808, a data storage unit 810, a data communication unit812, a graphical user interface 814, and a time reference unit 816.

In one embodiment, the electronic device 800 includes a power source 802that supplies power to components of the electronic device 800. Thepower unit 802 may include a battery to supply power and a charging unitthat charges the battery. Alternatively, electronic device 800 isconnectable to an energy source that powers the electronic device 800.In one embodiment, a charger may be used to recharge a battery or otherenergy source of the power source 802.

In another embodiment, the electronic device 800 includes a processingdevice 804. The processing device 804 may include a central processor toprocess the data and/or information of the other components that make upthe electronic device 800 or other units, interfaces, and/or devicesattached to or in communication with the electronic device 800.

In another embodiment, the electronic device 800 may include a sensorinterface unit 806. The sensor interface unit 806 may be coupled to oneor more sensors, such as the optical sensor, the impedance sensor, orthe humidity and/or temperature sensor, and may perform one or moremeasurements relating to a physiological condition of a body using theone or more of the sensors. In another embodiment, the sensor interface806 may be coupled to the processing device 804. The sensor interface806 can use the one or more sensors to take measurements relating to ahydration condition of a body, an impedance measurement, a temperatureof a body or of an environment, a humidity measurement of a body or ofan environment, or another physiological state or environment condition.In one example, the sensor interface 806 may be coupled to theprocessing device 804 and the optical sensor. In this example, thesensor interface unit 806 may receive data from the optical sensorrelating to a portion of light that was reflected off an artery or othermuscular-walled tube. Alternatively, the sensor interface 806 and theprocessing device 804 may be the same component. The sensor interfaceunit 806 may measure the backscatter of one or more wavelengths thathave been reflected off a vein, artery, or other muscular-walled tubeusing the portion of light.

In one embodiment, the electronic device 800 may include a timereference unit 816 that generates time reference data usable to controlthe time at which data is collected from the sensor interface unit 806.The time reference unit 816 may also be used to calculate spatial and/ortemporal derivatives between information received from the sensorinterface unit 806. In one embodiment of the disclosure, the timereference unit 816 may keep track of the calendar time, such as a clock.Alternatively, the time reference unit 816 may act as a timer, keepingtrack of a lapsed time or decrementing from a defined time to zero. Thetimer of the time reference unit 816 may be used to collect informationor data from the sensor interface 806 for a defined period of time or torecord how long the sensor interface 806 collects data.

In one embodiment, the electronic device 800 includes a data analysisunit 808. The data analysis unit 808 may be communicatively coupled tothe processing device 804, sensor interface unit 806, time referenceunit 816, and other components of the electronic device 800. The dataanalysis unit 808 may determine that a hydration condition has changedfor a user by comparing temporal data from the time reference unit 816to measurement data from the sensor interface unit 806. The dataanalysis unit 808 may communicate the hydration condition to a userthrough the graphical user interface (GUI) 814.

In one embodiment, the electronic device 800 includes a graphical userinterface 814. The graphical user interface may be a monitor screen,liquid crystal display (LCD), LED display, or the like. In aspect, theGUI may present information such as a hydration condition to the user.In another aspect, the user may be able to interact with the electronicdevice though inputs or icons on the GUI.

FIG. 9A illustrates a flow diagram of a method 900 of determining ahydration condition, according to one embodiment. The method 900 may beperformed by processing logic that may include hardware (e.g.,circuitry, dedicated logic, programmable logic, microcode, etc.),software (such as instruction run on a processing device, a generalpurpose computer system, or a dedicated machine, firmware, or acombination thereof. In one embodiment, the method 900 may be performed,in part, by processing logic of processing device 804.

For simplicity of explanation, the method 900 is depicted and describedas a series of acts. However, acts in accordance with this disclosurecan occur in various orders and/or concurrently and with other acts notpresented as described herein. Furthermore, not all illustrated acts maybe performed to implement the method 900 in accordance with thedisclosed subject matter. In addition, those skilled in the art willunderstand and appreciate that the method 900 could alternatively berepresented as a series of interrelated states via a state diagram orevents.

The method can include, emitting light, from a first light source (910).In one embodiment, the first light source can be coupled to a sensorinterface, where the sensor interface can turn the first light source onto emit light at a first location into the user. In another embodiment,the first light source can emit the light at a first wavelength. Inanother embodiment, the light source can be affixed to a body of a userto emit into a body of the user. The first wavelength may be a discretewavelength or a full spectrum of wavelengths. In one embodiment, thediscrete wavelength may be between 535 nanometers and 735 nanometers.The discrete wavelength 535 nanometers and 735 nanometers may correspondto a wavelength that is absorbed by sodium. In another embodiment, adiscrete wavelength may be between 680 nanometers and 880 nanometers.The discrete wavelength 680 nanometers and 880 nanometers may correspondto a wavelength that is absorbed by potassium. In another embodiment,the electronic device can include multiple light sources that emit lightat different wavelengths. For example, the electronic device can beinclude a first light source to emit light at a wavelength between 535nanometers and 735 nanometers and a second light source to emit light ata wavelength between 680 nanometers and 880 nanometers.

The method can include receiving, by the optical sensor, backscatter ofthe light from a depth below the surface of the body (920). In oneembodiment, the optical sensor may be positioned at a fixed distancefrom the light source to detect backscatter from a muscular-walled tubeof the body. A muscular-walled tube may be an artery or vein of thebody. The backscatter may be emitted from one or more light sources inblock 920 emitting one or more wavelengths.

The method can include, determining, by the processing device, an amountof backscatter of the light at the first wavelength (930). In oneembodiment, the processing device or sensor interface may receive thedetected backscatter from the optical sensor to perform thedetermination. In one embodiment, the processing device or opticalsensor may measure light of one or more wavelengths corresponding to oneor more substances in the blood stream or other tissue from one or morelight sources. In one embodiment, the processing device or sensorinterface will measure the amount of received backscatter of light of awavelength between 535 nanometers and 735 nanometers corresponding to ameasurement of a wavelength that is absorbed by sodium in the body. Inanother embodiment, the processing device or sensor interface willmeasure the amount of received backscatter of light of a wavelengthbetween 680 nanometers and 880 nanometers corresponding to a measurementof a wavelength that is absorbed by potassium in the body.

The method can include comparing, by the processing device or sensorinterface, the amount of backscatter of light of the first wavelength toa previous amount of backscatter of light of the first wavelength (940).In one embodiment, if the backscatter measurement of light of the firstwavelength is greater than a previous measurement of backscatter oflight of the first wavelength, it may indicate that that a concentrationof a substance in the body that corresponds to the light of the firstwavelength, such as sodium or potassium, has increased. In one example,an increase in the backscatter of light of the first wavelength mayindicate that the level of potassium or sodium in the bloodstream orother tissue has decreased.

The method can include, determining, by the processing device or sensorinterface, a hydration condition of the user when the amount of lightthat has backscattered changes (950). The hydration condition of a useris affected by the concentration of electrolytes in the body includingpotassium and sodium. For example, the processing device may determinethat the hydration condition of the user is a dehydration condition whenthe amount of sodium backscatter decreases from one measurement to thenext. In another example, the processing device may determine that thehydration condition of the user is a hydrated condition when the amountof sodium backscatter increases. Alternatively, the processing devicemay determine that the hydration condition of a user is stable if therehas not been a change in backscatter.

FIG. 9B illustrates a flow diagram of a method of determining a changein hydration condition of a user, according to one embodiment. Themethod 960 may be performed by processing logic that may includehardware (e.g., circuitry, dedicated logic, programmable logic,microcode, etc.), software (such as instruction run on a processingdevice, a general purpose computer system, or a dedicated machine,firmware, or a combination thereof. In one embodiment, the method 960may be performed, in part, by processing logic of processing device 804.

For simplicity of explanation, the method 960 is depicted and describedas a series of acts. However, acts in accordance with this disclosurecan occur in various orders and/or concurrently and with other acts notpresented as described herein. Furthermore, not all illustrated acts maybe performed to implement the method 960 in accordance with thedisclosed subject matter. In addition, those skilled in the art willunderstand and appreciate that the method 960 could alternatively berepresented as a series of interrelated states via a state diagram orevents.

The method begins by comparing the measurement of backscatter of lightof the first wavelength to an operating hydration condition of a user todetermine a hydration condition of a user (965). The first wavelength oflight may correlate to a wavelength of light absorbed by a substance,such as sodium, in the blood stream or in other tissue of the body ofthe user. A hydration condition of the user can include a dehydrated(hypo-hydrated), normal hydration level (euhydrated), or over-hydrated(hyper-hydrated) conditions. The backscatter measurement of the firstwavelength can be determined by the sensor interface as discussed in thepreceding paragraphs.

The method includes, determining, by the processing device, when thehydration condition of the user is below the operating hydrationcondition of the user by comparing the measurement of backscatter of thefirst wavelength to the operating hydration condition of the user (970).In one embodiment, the operating hydration condition of the user can bedetermined by taking multiple measurements over a period of time anddetermining a range in which the user is within the user's operatinghydration condition (e.g., euhydration condition).

In one embodiment, when the measurement of backscatter of light of thefirst wavelength is above the operating hydration condition, theprocessing device or sensor interface may determine that the user is indehydrated (hypo-hydrated) condition (980). If the measurement ofbackscatter of light of the first wavelength is not below the operatinghydration condition of the user, the processor may determine that theuser is not in a hypo-hydrated condition. The processor may determinewhen the hydration condition of the user is above the operatinghydration condition of the user (975). If the measurement of backscatterof light of the first wavelength above the normal operating hydrationcondition of the user, it may be an indicator that the user is in anover-hydrated (hyper-hydrated) condition (985). Alternatively, if theprocessing device or sensor interface determines that the user isneither above nor below the operating hydration condition of the user,that the user is maintaining their operating hydration condition andthat the user is in a healthy hydration (euhydrated) condition (990).

FIG. 10 illustrates an electronic device 1000 communicating with anexternal electronic device 1090, according to one embodiment. Theelectronic device 1000 can be a substantially circular band with anouter surface 1010 and an inner surface 1020. In one example, the outersurface 1010 or the inner surface 1020 can be made of flexible ornon-rigid material, such as rubber, polyurethane, and so forth. Inanother example, the outer surface 1010 or the inner surface 1020 can bemade of semi-rigid or rigid material, such as plastic, metal, and soforth. In another example, a portion of the outer surface 1010 or theinner surface 1020 can be the flexible or non-rigid material and aportion of the outer surface 1010 or the inner surface 1020 can be thesemi-rigid or rigid material. In another example, a portion of the innersurface 1020 that contacts a body of the user is a conductive material.For example, one or more sensors 1040 are bio-impedance sensors that areconductive rubber pads that contact the body of the user and are used byprocessing logic to make bio-impedance measurements.

In one example, a cavity or chamber 1045 can be between the outersurface 1010 and an inner surface 1020. The cavity or chamber 1045 caninclude modules, units, systems, subsystems, or devices of theelectronic device 1000. For example, the cavity or chamber 1045 canhouse a power source 1050, a graphical user interface or touchcontroller 1060, a communication unit 1070, a controller 1080, one ormore sensors 1040, and/or other units. In one example, the communicationunit 1070 can wirelessly communicate with an external electronic device1090. In another example, the power source 1050 can provide power toother units or modules of the electronic device 1000. In one example thetouch controller 1060 can receive user input from an input device. Inone example, the input device can be a graphical user interface (GUI) ora touch display and be operable to receive input via the GUI or thetouch display. In another example, the input device can receivecommunications from other devices via a communication network (e.g., awireless network) or a communication connection (such as a universalserial bus). In another example, the controller 1060 can control systemsand subsystems of the electronic device 1000.

In another example, the power source 1050 can be a battery, such as arechargeable battery. The power source 1050 can receive power fromanother power source such as via a cord plugged into a power source orusing wireless power such as inductive wireless charging or resonantwireless charging. In another example, the electronic device 1000 canhave one or multiple sensors 1040 (e.g., a sensor array). In oneexample, the multiple sensors 1040 can be different types of sensors.

In one example, the electronic device 1000 can receive physiologicalinformation such as a hydration condition and/or an environmentalcondition of a user of the electronic device 1000 from another device.In another example, the electronic device 1000 can have a touchcontroller 1060 to receive user input physiological information and/orenvironmental information. In one example, a power source 1050, a touchcontroller 1060, a communication unit 1070, a controller 1080, one ormore sensors 1040 can be in direct or indirect communication with eachother. For example, the touch controller 1060 receives user inputinformation from the input device and communicates the user inputinformation to the controller 1080. In this example, the controller 1080can include a processor or processing device to analyze or process theuser input information. In another example, the sensor 1040 can take aphysiological measurement and communicate physiological information tothe external electronic device 1090 via the communication unit 1070. Inone embodiment, the external electronic device 1090 is an electronicdevice with a processor, such as a smartphone, electronic tablet, orpersonal computer. In another embodiment, the external electronic device1090 is a cloud computing system or a server. The external electronicdevice 1090 can analyze or process data or information received from theelectronic device 1000. In one example, the external electronic device1090 can store the processed data or information. In another example,the external electronic device 1090 can send the processed data orinformation back to the electronic device 1000.

FIG. 11 illustrates an interior view of the electronic device 1100,according to one embodiment. The electronic device 1100 may include abottom side 1101 and a top side 1102. In one embodiment, the electronicdevice 1100 may have a flume extending from the bottom side 1101 to thetop side 1102. The fluke may allow humidity and/or temperature sensors1105 to detect the humidity and temperature of both the air and the skinof the user.

In one embodiment, the electronic device 1100 may include a flexiblecircuit board 1180 with an upper section 1120 and a lower section 1150.The upper section 1120 of the flexible circuit board 1180 may include amotion processing unit (MPU) 1125, display LEDs or a graphical userinterface 1130, and one or more communication components 1135, such as aBluetooth Low Energy (BLE) component. In one embodiment, the MPU maydetect movement of electronic device and relay motion information to thesensor interface unit 806. Additionally, display LEDs or GUI 1130 may beused to inform the user of a hydration condition. The lower section 1150of the electronic device 1100 may include a thermistor 1175, opticalcomponents 1165 including an optical sensor and one or more lightsources, impedance sensor contacts 1170, and a vibrator 1160. In oneembodiment, the vibrator 1160 may be utilized to inform the user when ahydration condition has changed or to provide additional relevantinformation to the user.

FIG. 12A illustrates an optical sensor 1210 and multiple light sources1220, 1222, and 1224 embedded into the electronic device 1200, accordingto one embodiment. In one embodiment, the electronic device 1200 mayinclude light sources 1220 on one side of the optical sensor 1210 andlight sources 1222 and 1224 on the other side of the optical sensor1210. In some embodiments, the light sources 1220, 1222, and 1224 may behermetically seals, e.g. airtight, water proof, sweat proof, dust proof,and so forth. Waterproofing rings 1230 and 1232 or other sealants may beused to hermetically seal the interior of the electronic device 1200. Insome embodiments, other components such as the optical sensor 1210 maybe hermetically sealed using waterproofing rings or other sealants toprevent water, sweat, dust, and other debris from entering the interiorof the electronic device 1200.

FIG. 12B illustrates a cross sectional view of multiple light sources1226 and 1228 embedded into an electrical device 1200, according to oneembodiment. In one embodiment, light sources 1226 and 1228 may bepositioned on one side of an artery or vein and may emit light of awavelength corresponding to a wavelength absorbed by a substance of thebody into the body of a user. In this example, light sources 1226 and1228 may be hermetically sealed using waterproofing rings 1234 and 1236.Waterproofing ring 1234 and 1236 may prevent moisture from entering intothe electrical device and reaching a circuit board 1240.

FIG. 13 illustrates an electronic device 1300 in direct communicationswith a computing device 1320, according to one embodiment. In oneexample, sensor measurements collected and/or stored by the electronicdevice 1310 can be processed or analyzed by a processor or processingdevice of the electronic device 1300 and/or by a computing device 1320in communication with the electronic device 1300. The electronic device1300 can be in direct communication 1330 with the computing device 1320.In one example, the direct communication 1330 can be a Bluetooth®communication link, a Zigbee® communication link, radio signal, or otherdirect communication systems. In another example, the other computingdevice 1320 can be a server that stores information, such as sensormeasurements or hydration condition information previously taken by theelectronic device 1310 or sensor measurements or hydration conditioninformation taken from a group of individuals, as discussed herein. Inanother example, the computing device 1320 can be a mobile computerdevice, such as a laptop computer, tablet, or a smartphone. Theelectronic device 1300 can communicate information, such as sensormeasurements or hydration condition information, to the computing device1320. In one example, the computing device 1320 can process and/oranalyze the sensor measurements and/or information received from theelectronic device 1300. In another example, the computing device 1320can send processed data, analyzed data, measurement results, and/orother information to the electronic device 1300. In another example, thecomputing device 1320 can communicate calibration information to theelectronic device 1310.

FIG. 14 illustrates an electronic device 1400 and a computing device1420 in indirect communication using a communications network accordingto one embodiment. In one embodiment, the electronic device 1400 can bea standalone device with a processing device to analyze or process:information taken from one or more sensors 1450 of the electronic device1400; information received from other devices; and/or information storedin a memory of the electronic device 1400.

In another embodiment, the electronic device 1400 communicates locallywith the computing device 1420 use a wireless communication network 1430or a cellular communication network 1440. The local computing device1420 can be a smartphone, tablet device, personal computer, laptop, alocal server, and so forth. In another embodiment, the electronic device1400 communicates with a non-local or remote computing device 1420 usinga wireless communication network 1430 or a cellular communicationnetwork 1440. The non-local or remote computing device 1420 can be aremote server, a cloud-based server, a back-end server, or other remoteelectronic devices.

In one example, the wireless communication network 1430 is a cellularnetwork employing a third generation partnership project (3GPP) release8, 9, 10, 11, or 12 or Institute of Electronics and Electrical Engineers(IEEE) 802.16p, 802.16n, 802.16m-2011, 802.16h-2010, 802.16j-2009,802.16-2009. In another example, the electronic device 1400 may providea secure wireless area network (WLAN), secure PAN, or wireless fidelity(Wi-Fi) Private Wireless Wide Area Network (PWAN) to communicate withthe computing device 1420. The electronic device 1400 in the WLAN mayuse the Wi-Fi® technology and IEEE 802.11 standards defined by the Wi-FiAlliance® such as the IEEE 802.11-2012, IEEE 802.11ac, or IEEE 802.11adstandards. Alternatively, the electronic device 1400 and the computingdevice 1420 in the WLAN may use other technologies and standards.Similarly, the electronic device 1400 in the PAN or WPAN may use aBluetooth® technology and IEEE 802.15 standards defined by the BluetoothSpecial Interest Group, such as Bluetooth v1.0, Bluetooth v2.0,Bluetooth v3.0, or Bluetooth v4.0 (including Bluetooth low energy).Alternatively, the electronic device 1400 in the secure PAN may useother technologies and standards. In another embodiment, thecommunications network may be a Zigbee® connection developed by theZigBee Alliance such as IEEE 802.15.4-2003 (Zigbee 2003), IEEE802.15.4-2006 (Zigbee 2006), IEEE 802.15.4-2007 (Zigbee Pro). The WAN orPWAN can be used to transmit data over long distances and betweendifferent LANs, WLANs, metropolitan area networks (MANs), or otherlocalized computer networking architectures.

The electronic device 1400 and the computing device 1420 can be inindirect communication using a communications network such as wirelesscommunication network 1430 (such as a Wi-Fi® network) and/or using acellular communication network 1440 (such as a 3rd GenerationPartnership Project (3GPP®) network) to communicate data or measurementinformation. In one example, the electronic device 1400 can take sensormeasurements using a sensors 1450 and communicate the sensormeasurements to the computing device 1420 via the wireless communicationnetwork 1430 and/or the cellular communication network 1440. In anotherexample, the computing device 1420 can receive sensor measurements fromthe electronic device 1400 via the wireless communication network 1430and/or the cellular communication network 1440 and process the sensormeasurements and/or analyze the sensor measurements. When the computingdevice 1420 has processed the sensor measurements and/or analyzed thesensor measurements, the computing device 1420 can communicate theprocessed sensor measurements, analyzed sensor measurements, sensormeasurement results, or other information to the electronic device 1400via the wireless communication network 1430 and/or the cellularcommunication network 1440.

FIG. 15 depicts a body area network (BAN) devices 1562-1576communicating using a BAN, according to one embodiment. In oneembodiment, the BAN can include a wired body area network, a wirelessbody area network (WBAN), and/or a body sensor network (BSN). The BANcan include multiple wearable computing devices or wearable sensordevices 1562-1576 that are in communication with each other to send andreceive data and information. In one example, the BAN devices caninclude: a BAN device 1560 that is attached or coupled to the body ofthe user; an BAN device 1562 that is implanted into the body of theuser; a BAN device 1568 that is embedded into the body of a user; a BANdevice 1570 that is mounted on a surface of the body, and so forth. Inanother example, the BAN devices can include devices adjacent the userincluding: a BAN device 1564 shaped to fit in a clothes pockets of theuser, a BAN device 1566 that a user can carry, such as a handhelddevice; a BAN device 1572 that is integrated into clothes of the user; aBAN device 1576 located in a user's bag, a BAN device 1574 integratedinto a user's bag, and so forth. In one embodiment, an electronic deviceis a BAN device. In another embodiment, the BAN devices 1562-1576 can bebody sensor units (BSUs) that include a processing device, a sensor, anda communication device. The BSUs can communicate with a body centralunit (BCU) 1578 that is a hub for the BAN devices. The BCU 1578 can belocated at any of the locations discussed above for the BAN devices1562-1576. The BCU 1578 can include a processing device, memory, acommunication device, and a display. The BCU 1578 can receive data froma BAN device 1562-1576 and analyze the data. In one example, the BCU1578 can display the analyzed data using the display of the BCU 1578. Inanother example, the BCU 1578 can send the analyzed data to a BAN device1562-1576 or another device. One advantage of the BCU 1578 communicatingwith the BAN devices 1562-1578 is that the BAN devices 1562-1578 can beconfigured to be minimal sensor devices with low power consumption and acompact design where the BCU 1578 performs the processing of the data.

In another embodiment, the BCU 1578 can be a data hub or data gateway tomanage the BAN devices 1562-1576. In another embodiment, the BCU 1578can provide a user interface to control the BAN devices 1562-1576. Inanother embodiment, the BAN devices 1562-1576 and/or the BCU 1578 canuse wireless private area networks (WPAN) technology as a gateway orrelay to reach longer ranges. In one example, the BCU 1578 can us a WPANto connect the BAN device 1562-1576 on the body to the internet. Forexample, medical professionals can access patient data from the BANdevices 1562-1576 online using the internet independent of a location ofa patient.

FIG. 16 depicts a schematic view of an electronic device 1610, accordingto one embodiment. The electronic device 1610 may include the indicators1618, a sensor array 1622 (to include at least one of the sensors inFIG. 1, 2, 4, 5, or 7), a processing device 1655, a communicationsinterface 1660, an antenna 1662 coupled with the communicationsinterface 1660, external sensors 1664, and accompanying antenna(s) 1666.In one example, the sensor array 1622 may include one or morephysiological sensors to take physiological measurements (e.g.,measurements related to the body of the individual or animal). Thesensor array 1622 may include one or more sensors to engage a user ofthe electronic device to take measurements. In various examples, thesensor array 1622 may include, without limitation: a bio-impedancespectroscopy sensor 1668 (or simply impedance sensor 1668), an opticalsensor 1670, an electrocardiogram (ECG) sensor 1672, a temperaturesensor 1674 (such as a thermometer or thermistor), an accelerometer1676, a spectrometer 1678, a sweat rate sensor 1680, and so forth. Inone example, the sensor array 1622 can contact or engage the body of theuser at a location 1682.

FIG. 17 is a block diagram of the electronic device 1700 with acorrelator 1713, a baseliner 1715, and an alerter 1717, according to oneembodiment. The electronic device 1700 may include, without limitation,one or more physiological sensor(s) 1702, one or more Newtoniansensor(s) 1704, one or more environmental sensor(s) 1705, one or morelocation sensor(s) 1704, a processor 1003, a memory device 1708, adisplay 1780, a communication interface 1790 (such as a radio frequency(RF) circuit), and an antenna 1792 coupled to the communicationinterface 1790.

In one embodiment, the communication interface 1790 may communicate, viathe antenna 1792, with an external electronic device 1090 (illustratedin FIG. 10), a computing device 1320 or 1420 (illustrated in FIGS. 13and 14), and with other wireless devices. In one example, thecommunication interface 1790 may communicate the information using acellular network, a wireless network, or a combination thereof. In oneexample, the communications network can be a cellular network employinga third generation partnership project (3GPP) release 8, 9, 10, 11, or12 or Institute of Electronics and Electrical Engineers (IEEE) 802.16p,802.16n, 802.16m-2011, 802.16h-2010, 802.16j-2009, 802.16-2009. Inanother example, the electronic device 1700 may provide a securewireless area network (WLAN), secure PAN, or wireless fidelity (Wi-Fi)Private Wireless Wide Area Network (PWAN) to communicate with a device.The electronic device 1700 in the WLAN may use the Wi-Fi® technology andIEEE 802.11 standards defined by the Wi-Fi Alliance® such as the IEEE802.11-2012, IEEE 802.11ac, or IEEE 802.11ad standards. Alternatively,the devices in the WLAN may use other technologies and standards.Similarly, the electronic device 1700 in the PAN or WPAN may use theBluetooth® technology and IEEE 802.15 standards defined by the BluetoothSpecial Interest Group, such as Bluetooth v1.0, Bluetooth v2.0,Bluetooth v3.0, or Bluetooth v4.0. Alternatively, the electronic device1700 in the secure PAN may use other technologies and standards. Inanother embodiment, the communications network may be a Zigbee®connection developed by the ZigBee Alliance such as IEEE 802.15.4-2003(Zigbee 2003), IEEE 802.15.4-2006 (Zigbee 2006), IEEE 802.15.4-2007(Zigbee Pro). The WAN or PWAN can be used to transmit data over longdistances and between different LANs, WLANs, metropolitan area networks(MANs), or other localized computer networking architectures.

In one embodiment, the electronic device 1700 can communicate data withthe other devices via another device, such as a smartphone or tabletcomputing device. For example, the communication interface 1790 can pairwith a smartphone via the wireless network. The smartphone can receivedata using the wireless network and can communicate the data to theother device. In another embodiment, the electronic device 1700 maycommunicate information with the other device via repeaters or a relaysystem. For example, a user of the electronic device 1700 can be outsidea coverage area for the cellular network or the wireless network, e.g.,a farm worker out in the field. In this example, the electronic device1700 can determine that it is outside the coverage area and switch tocommunicating via the repeaters or the relay system.

In one embodiment, the electronic device 1700 can determine it isoutside a coverage area when it does not receive a signal from thecellular network or the wireless network. In another embodiment, theelectronic device 1700 can ping the cellular network or the wirelessnetwork (such as a tower within the cellular network or the wirelessnetwork) and determine that it is outside the coverage area when theelectronic device 1700 does not receive a reply to the ping. In anotherembodiment, multiple electronic devices 1710 can communicate with eachother to form a piconet. In this embodiment, a first electronic devicecan determine it is outside the coverage area and can scan for a secondelectronic device, where the second electronic device is in the coveragearea or in communication with another electronic device in the coveragearea. When the first wearable safety finds the second electronic device,the electronic device can communicate information to an end device or tothe cellular network or the wireless network via the second electronicdevice.

The processor 1703 may include a first sensor interface 1707 forreceiving sensor data from the physiological sensor(s) 1702, a secondsensor interface 1708 for receiving sensor data from the Newtoniansensor(s) 1704, a third sensor interface 1709 for receiving sensor datafrom the environmental sensor(s) 1705, a fourth sensor interface 1710for receiving sensor data from the location sensor(s) 1706, and aprocessing element 1711. The processing element 1711 in turn may includea correlator 1713, a baseliner 1715 and/or an alerter 1717. The memorydevice 1708 may also include, without limitation, a sensor module 1716,physiological data 1724, environmental data 1726, Newtonian data 1728,and profile data 1730, location data 1732.

The electronic device 1700 may include the sensor array 120 (FIG. 1)with two or more sensors. In the depicted embodiment, the electronicdevice 1700 may include one or more physiological sensors 1702, one ormore Newtonian sensors 1704, one or more environmental sensors 1705, oneor more location sensors 1706, or a combination thereof. In someinstances, the Newtonian sensors 1704 may be physiological sensors. Thatis, in some embodiment, the activity level may be determined from one ormore physiological measurements.

A physiological measurement may be any measurement related to a livingbody, such as a human's body or an animal's body. The physiologicalmeasurement is a measurement made to assess body functions.Physiological measurements may be simple, such as the measurement ofbody or skin temperature, or they may be more complicated, for examplemeasuring how well the heart is functioning by taking an ECG(electrocardiograph), or determining a hydration condition of the body.Physiological measurements may also include motion and/or movement ofthe body. In some cases, these physiological measurements may be takenas an aggregate, e.g., as physiological data, with which to correlate toother physiological measurements, a physiological parameter, and/or anenvironmental parameter.

A parameter may be considered a measurable quantity (such as heart rate,temperature, altitude, and oxygen level, as just a few examples). Whenmeasurements of parameters are taken in the aggregate, the measurementsmay form data which may be analyzed and correlated to other data orparameters, to identify trends or to identify when meeting (orexceeding) certain thresholds that trigger alerts or other actions andthe like.

The physiological sensors 1702 may include a pulse oximeter sensor, anelectrocardiography (ECG) sensor, a fluid level sensor, an oxygensaturation sensor, a body core temperature sensor, a skin temperaturesensor, a plethysmograph sensor, a respiration sensor, a breath ratesensor, a cardiac sensor (e.g., a blood pressure sensor, a heart ratesensor, a cardiac stress sensor, or the like), an impedance sensor(e.g., bio-impedance spectroscopy sensor), an optical sensor, aspectrographic sensor, an oxygen saturation sensor, or a sweat ratesensor. Alternatively, other types of sensors may be used to measurephysiological measurements, including measurements to determine activitylevels of a person wearing the electronic device.

The Newtonian sensors 1704 may be any of the physiological sensorsdescribed above, but in some cases, the Newtonian sensors 1704 areactivity or motion sensors, such as, for example, a gyroscope sensor, avibration sensor, an accelerometer sensor (e.g., a sensor that measuresacceleration and de-acceleration), a three dimensional (3D)accelerometer sensor (e.g., sensors that measure the acceleration andde-acceleration and the direction of such acceleration andde-acceleration), a force sensor, a pedometer, a strain gauge, amagnetometer, and a geomagnetic field sensor that may be used foractivity level measurements; whereas the physiological sensors 1702 maybe used for specific physiological measurements.

In one embodiment, an environmental measurement may be any measurementof an area approximate or adjacent a user. The environmental sensors1705 may be a humidity sensor, an ambient temperature sensor, analtitude sensor, a barometer, and so forth. A location measurement maybe any measurement of a location of the user or a movement of the user.The location sensor 1706 may be a global positioning system (GPS), atriangulation system, or a location sensor. One or a combination of thephysiological data 1724, the environmental data 1726, the Newtonian data1728, the profile data 1730, and the location data 1732 may be obtainedfrom other sources such as through network from sources reachable in thecloud or online.

In another embodiment, the environmental measurement can be anymeasurement of a local or central location measurement of where a useris located. For example, one or more environmental sensors 1705 may belocated at a location within a threshold radius of the user, such as athreshold radius from the user location. In this example, theenvironmental sensors 1705 can take environmental measurements and relaythe information to the electronic device 1700 or to a communication hubthat has a communication channel established with the electronic device1700. Alternatively, the environmental sensors 1705 can takeenvironmental measurements and relay the information to a processing hubthat can analyze the environmental measurements to determine selectedenvironmental factors (such as a humidity level, a heat index, and soforth) and can communicate the environmental factors to the electronicdevice 1700 or to another electronic device. In another embodiment, theprocessing hub can receive the environmental measurements from theenvironmental sensors 1705 and other measurements (such as physiologicalmeasurements) from the electronic device 1700. The processing hub cananalyze the environmental measurements and the other measurements todetermine selected result data, such as a hydration level of a user or ahealth level of the user. In another embodiment, the electronic device1700 can take a first set of environmental measurements and the localenvironmental sensors 1705 can take a second set of environmentalmeasurements. The first set of environmental measurements and the set ofenvironmental measurements can be combined or aggregated and theprocessing hub and/or the electronic device 1700 can analyze theaggregated environmental measurements.

In another embodiment, the environmental measurements can be from anenvironmental information outlet or provider. For example, theenvironmental information outlet or provider is a weather station, anews station, a television station, an online website, and so forth. Theelectronic device 1700 or the processing hub can receive theenvironmental information from the environmental information outlet orprovider can use the environmental information to determine selectedphysiological and/or environmental data or factors.

The first sensor interface 1707 may be coupled with the one or morephysiological sensors 1702, a second sensor interface 1708 may becoupled with the one or more Newtonian sensors 1704, a third sensorinterface 1709 may be coupled with the one or more environmental sensors1705, and a fourth sensor interface 1710 may be coupled with the one ormore location sensors 1706. The processing element 1711 may be operableto execute one or more instructions stored in the memory device 1708,which may be coupled with the processor 1703. In some cases theprocessing element 1711 and memory device 1708 may be located on acommon substrate or on a same integrated circuit die. Alternatively, thecomponents described herein may be integrated in one or more integratedcircuits as would be appreciated by one having the benefit of thisdisclosure. The memory device 1708 may be any type of memory device,including non-volatile memory, volatile memory, or the like. Althoughnot separately illustrated the memory device may be one or more types ofmemory configured in various types of memory hierarchies.

The memory device 1708 may store physiological data 1724, such ascurrent and past physiological measurements, as well as profile data1730, including user profile data, bibliographic data, demographic data,and the like. The physiological data 1724, and in some cases the profiledata 1730, may also include processed data regarding the measurements,such as statistical information regarding the measurements, as well asdata derived from the measurements, such as predictive indicators,results, and/or recommendations.

In one example, the profile data 1730 may also include informationconnected to user profiles of the users that wear the electronic device1700, such as a gender of the user, an age of the user, a body weight ormass of the user, a health status of the user, a fitness level of theuser, or a family health history of the user. In another example, theprofile data 1730 can include occupational information of the users thatwear the electronic device 1700, such as a job type, a job title,whether the job is performed indoors or outdoors, a danger level of thejob, and so forth. For example, the job types can include an elderlylive-at-home job, an oil driller, a construction worker, a railroadworker, a coal mine worker, a job in confined spaces, a fireman, aconstruction worker, an outdoor worker, an office worker, a truckdriver, a child, or a disabled individual.

In one example, the electronic device 1700 can receive the profile data1730 via a touch screen device integrated into the electronic device1700 or coupled to the electronic device 1700. In another example, theelectronic device 1700 can receive the profile data 1730 via acommunication port of the electronic device 1700. For example, theelectronic device 1700 can receive profile data 1730 from another devicevia a wired communication connection (e.g., a universal serial bus) orvia a wireless communication connection (e.g., a Bluetooth®communication technology).

The profile data 1730 may also be linked to various physiological data1724 and Newtonian data 1728 and be tracked over time for the users. Theprofile data 1730 may also include baselines of physiological parametersfor respective users. In one example, the baselines are of a heart rate,a blood pressure, bio-impedance, skin temperature, oxygen levels,hydration levels, electrolyte levels and so forth. When the baselinesare included with the user profiles, the user profiles may be referredto as baseline profiles for the respective users.

The memory device 1708 may also store one or a combination of theenvironmental data 1726, the Newtonian data 1728, the profile data 1730,and the location data 1732. The Newtonian data 1728, environmental data1726, or location data 1732 may be current and past measurements, aswell predictive data for predictive modeling of activity levels,environmental levels, or locations. The memory device 1708 may storeinstructions of the sensor module 1716 and instructions and data relatedto the correlator 1713, the baseliner 1715 and the alerter 1717, whichperform various operations described below.

In particular, the sensor module 1716 may perform operations to controlthe physiological sensors 1702, Newtonian sensors 1704, environmentalsensors 1705, and location sensors 1706, such as when to turn them onand off, when to take a measurement, how many measurements to take, howoften to perform measurements, etc. For example, the sensor module 1716may be programmed to measure a set of physiological measurementsaccording to a default pattern or other adaptive patterns to adjust whenand how often to take certain types of measurements. The measurementsmay be stored as the physiological data 1724, the environment data 1726,and the Newtonian data 1728, location data 1732, and some of them mayalso be integrated as a part of the profile data 1730, as discussed.

In the depicted embodiment, the processing element 1703 (e.g., one ormore processor cores, a digital signal processor, or the like) executesthe instructions of the sensor module 1716 and those related to thecorrelator 1713, the baseliner 1715, the alerter 1717 and possibly othermodules or routines. Alternatively, the operations of the sensor module1716 and the correlator 1713, the baseliner 1715, and the alerter 1717may be integrated into an operating system that is executed by theprocessor 1703. In one embodiment, the processing element 1711 measuresa physiological measurement via the first sensor interface 1707. Theprocessing element 1711 may measure an amount of activity of theelectronic device 1700 via the second sensor interface 1709. The amountof activity could be movement or motion of the electronic device 1700(e.g., by tracking location), as well as other measurements indicativeof the activity level of a user, such as heart rate, body temperature,skin luminosity, or the like. The processing element 1711 measures anenvironmental measurement via the third sensor interface 1709. Theprocessing element 1711 measures a location measurement via the fourthsensor interface 1710.

In one embodiment, the Newtonian sensors 1704 may include a hardwaremotion sensor to measure at least one of movement or motion of theelectronic device 1700. The processing element 1711 may determine theamount of activity based the movement or motion of the electronic device1700. The hardware motion sensor may be an accelerometer sensor, agyroscope sensor, a magnetometer, a GPS sensor, a location sensor, avibration sensor, a 3D accelerometer sensor, a force sensor, apedometer, a strain gauge, a magnetometer, and a geomagnetic fieldsensor.

The processor 1703 may further execute instructions to facilitateoperations of the electronic device 1700 that receive, store and analyzemeasurement data, environmental data, location data, and profile data.The indicator(s) 1718 may include one or more of a light, a display, aspeaker, a vibrator, and a touch display, useable to alert the user totake actions in response to trending levels of: physiological parametersduring or after physical activity and/or prepare for undertakinganticipated physical activity; environmental parameters; activityparameters, or location parameters.

In some embodiments, for example, the correlator 1713 may analyzemeasurement data to correlate physiological data, environmental data,activity data, location data, or user experienced feedback with aphysiological parameter, environmental parameter, activity parameter, alocation parameter, or user experienced feedback to predict a change ina level of the physiological parameter, environmental parameter,activity parameter, or a location parameter. In one embodiment, the userexperienced feedback can be physiological or psychological symptomsexperienced by the user. For example the physiological or psychologicalsymptoms can include: headaches, dizziness, tiredness, mental fatigue,increased thirst, dry mouth, swollen tongue, physical weakness,confusion, sluggishness, and so forth.

Such prediction may enable timely and accurate recommendations to a userin terms of hydrating, adjusting effort levels or other specific actionsto address a trend or a change in the physiological parameter, theenvironmental parameter, the activity parameter, or the locationparameter. The recommendations may be displayed in the display 1780,sent via an alert through one of the indictor(s) 1718 or displayed inanother device such as a smart phone or tablet or other computingdevice.

In another embodiment, the correlator 1713 may also track and analyzeNewtonian data of the user related to physiological or determinedparameters (such as heart rate, oxygenation, skin luminosity, hydration,and the like), related to location and type of activity (such asactivity levels associated with being at the gym, riding a bike,attending class, working at a desk, sleeping, or driving in traffic, andthe like) and/or related to scheduling information (such as appointmentson a calendar, invites received from friends, or messages related totravel and/or activity plans, and the like). Through this analysis, theelectronic device 1700 may track activity data over time, intelligentlyand continuously (or periodically) analyze all of this information, andalert the user through the indicator(s) 1718 to take a specific actionat a proper time before a start of a dehydration condition. The specificaction may include to hydrate extra hours before physical activity andto eat at least two hours before any physical activity, or other suchtiming that may be general to most users, or customized to a training ornutrition routine of a specific user.

In another embodiment, the correlator 1713 can build an individualizedprofile for the user. The correlator 1713 can receive the individualizedprofile information from an input device of the electronic device 1700.For example, the correlator 1713 can receive the individualized profileinformation from a touch screen of the electronic device 1700. Inanother example, the correlator 1713 can receive the individualizedprofile information from a device in communication with the electronicdevice (such as via a USB port or using a Bluetooth® technology). Inanother embodiment, the electronic device 1700 can include a memory thatstores the individualized profile information for the user.

The individualized profile can include physiological informationassociated with the user. For example, the physiological information caninclude a hydration condition, an average heart rate of the user, an ageof the user, a health level of the user, and so forth. Theindividualized profile can also include information associated with alocation or environment that the user is located. For example, theindividualized profile can include: humidity level information, such aswhen the user is located in a dry climate or in a humid climate;altitude level information, such as when the user is located at arelatively high altitude or a relatively low altitude; seasonalinformation, such as if it is winter where the user is located orsummer. The correlator 1713 can also determine an environmental effecton the user for the location where the user is located at. For example,if the user is located at their home that is at a high altitude with adry climate and it is a winter season, the correlator 1713 can determinethat the user is acclimated to high altitudes, dry climates, and thewinter season. The correlator 1713 can also update the user profile whenthe user changes location. For example, when the user leaves their homelocation and goes on a vacation to a location that is at a low altitude,a humid climate, and it is a summer season, the correlator 1713 candetermine that the user is not acclimated to the low altitude, humidclimate, and summer season.

In one embodiment, the electronic device 1700 can alert the user of thechanges to the individualized profile. In another embodiment, theelectronic device 1700 can alert the user of the changes to effectsassociated with the changes to the individualized profile. For example,the electronic device 1700 can access a table of predetermine effects ofthe user changing their user profile. In one example, the table canindicate that when the user switches from a low altitude to a highaltitude location, the user may experience altitude sickness. In anotherexample, the table can indicate that when the user switches from a dryclimate to a humid climate location, an ability of the user's body tocool itself down when an ambient temperature is relatively high. Inanother embodiment, the table can indicate when the current user profileindicates safety risks or physiological performance changes.

In another embodiment, the individualized profile can also includeinformation associated with clothing or apparel worn by the user of theelectronic device 1700. For example, the individualized profile canindicate that a user may wear different types of apparel for differentenvironments including: a thickness of fabric; a type of a fabric, suchas wool or cotton; a number of clothes layers worn by the client;accessories worn by the client, such as hard hats, steeled toed shoes,safety googles, safety belts, and so forth; and gender types of apparel,such as women and men's apparel. In one example, the correlator canadjust measurement information or measurement results based on thedifferent types of clothing or apparel. For example, the correlator 1713can determine that the user is a firefighter and is wearing multiplelayers of clothing to protect against fire. In this example, thecorrelator 1713 can determine that a cause of a hydration level of theuser decreasing is the multiple layers of clothing cause the firefighterto sweat more and loss more fluid than a typical number of layers ofclothing worn by the user.

In one embodiment, the alerter 1717 may decide the most appropriatetiming and mode of alert, whether through one of the indicator(s) 1718,the display 1780 or another device such as a smart phone, tablet or thelike. The type of indicator used to alert the user may also becustomized to or by the user.

In one embodiment, the correlator 1713 may determine a correlationbetween different data points or data sets of the input data (such asdata collected from different sensors, devices, or obtained from thecloud or online). The correlator 1713 may determine different types ofcorrelations of the data points or data sets. In one example, thecorrelator 1713 may execute a Pearson product moment correlationcoefficient algorithm to measure the extent to which two variables ofinput data may be related. In another example, the correlator 1713 maydetermine relations between variables of input data based on asimilarity of rankings of different data points. In another example, thecorrelator 1713 may use a multiple regression algorithm to determine acorrelation between a data set or a data point that may be defined as adependent variable and one or more other data sets or other data pointsdefined as independent variables. In another example, the correlator1713 may determine a correlation between different categories orinformation types in the input data.

In further examples, when the correlator 1713 determines a correlationbetween the different data points or data sets, the correlator 1713 mayuse the correlation information to predict when a first event orcondition may occur based on a second event or condition occurring. Inanother example, when the correlator 1713 determines a correlationbetween the different data points or data sets, the correlator 1713 mayuse the correlation information to determine a hydration condition. Asdiscussed in the preceding paragraphs, a hydration can be an event thatnegatively impacts a user's safety or health. In another example, whenthe correlator 1713 determines a correlation between the different datapoints or data sets, the correlator 1713 may use the correlationinformation to determine a cause of a condition and/or event, such as ahydration condition.

Additionally, or alternatively, the correlator 1713 may determine acorrelation between physiological data 1724, environmental data 1726,Newtonian data 1728, profile data 1730, and location data 1732. Forexample, the input data may include hydration level data (physiologicaldata) and ambient temperature data (environmental data). In thisexample, the correlator 1713 may identify a correlation between anincrease in the ambient temperature, a decrease in a hydration level ofa user, and a heat stroke. The correlator 1713 may identify thecorrelation between the ambient temperature, the hydration level, andthe heat stroke by using a regression algorithm with the heat stroke asan independent variable and the ambient temperature and the hydrationlevel as dependent variables. When the correlator 1713 has identifiedthe correlation between the heat stroke, the ambient temperature, andthe hydration level, the correlator 1713 may predict a heat stroke basedon a change in a hydration level of a user or a rate of change of ahydration level of a user and a change in the ambient temperature or arate of change in the ambient temperature.

Additionally, or alternatively, the correlator 1713 may determine acorrelation between a fatigue event, an altitude level, and anoxygenation level of a user. For example, the correlator 1713 maydetermine a correlation between an increase in the altitude level, adecrease in the oxygenation level of the user, and an increase in afatigue event. When the correlator 1713 determines the correlationbetween the altitude level, the oxygenation level, and the fatigueevent, the correlator 1713 may predict an increase or decrease in aprobability of a hydration condition change based on a change in theoxygenation level of user and the altitude level at which the user iscurrently at. In one example, the correlator 1713 can use theindividualized profile information (as discussed in the precedingparagraphs) of the user to determine the predicted increase or decreasein the probability of a hydration condition change. For example, thecorrelator 1713 can determine a change in altitude level of the userfrom a relatively low altitude to a relatively high altitude. Thecorrelator 1713 can use the individualized profile information todetermine that the user is acclimated to the relatively high altitude(such as if they live at a high altitude) and adjust the predictedincrease or decrease in the probability of a hydration condition changefor the change in altitude in view of the individualized profileinformation. For example, the correlator 1713 can predict that thechange from the low altitude to the high altitude will not increase ordecrease the probability of a user becoming dehydrated.

In a further example, the correlator 1713 may identify a correlationbetween location information and physiological data of a user. Forexample, the correlator 1713 may determine a location of a user for at aperiod of time, such as by using GPS sensor data or triangulation sensordata. In this example, the correlator 1713 may receive physiologicalmeasurement data (such as heart rate measurement data, opticalspectroscopy data, hydration level measurement data, blood pressuremeasurement data, and so forth). The correlator 1713 may correlate thelocation of the user with the physiological measurement data to increasean accuracy of data analysis, a diagnosis, or result data and/or provideadditional details regarding a cause of a change in a hydrationcondition.

In one example, the correlator 1713 may determine that a user is at workin an office location. When the correlator 1713 detects an increase in aheart rate or a blood pressure of a user, the correlator 1713 maycorrelate heart rate or blood pressure data and the location informationto determine a cause of the cognitive ability reduction event. Forexample, when a heart rate or blood pressure of an individual increaseswhile at a work in an office, the correlator 1713 may determine that theheart rate or blood pressure increase may be due to psychological causes(such as stress) rather than physiological causes (such as exercising orworking out) because the user is at a location where an individual isnot likely to physically exert himself or herself.

In another example, the correlator 1713 may determine an occupation ofthe user, such as by using the profile data 1730. In one embodiment, thecorrelator 1713 can determinate that the occupation of the user is ahigher risk occupation (e.g., a statistically more dangerousoccupation). For example, the correlator 1713 can access a database orlist (stored at the memory device 1708 or externally) that includesinformation associated with an occupation, such as environmentalexposure. When the correlator 1713 detects that the occupation of theuser is a higher risk occupation (e.g., an occupation with a risk levelthat exceeds a threshold value), the correlator 1713 may correlate heartrate data, blood pressure data, hydration level data, with theoccupational information to determine a cause of a hydration conditionchange. For example, when a heart rate and blood pressure of anindividual increases and a hydration level of the individual decreaseswhile the individual is working at an oil refinery or on a farm, thecorrelator 1713 may determine that the heart rate or blood pressureincrease may be due to physiological influences of the occupation (suchas strenuous labor or no breaks) rather than psychological causes (suchas stress) because the occupation where the individual is working at islikely to include physical exertion.

In a further example, the correlator 1713 may use a multiple regressionalgorithm to determine a correlation between multiple data points ordata sets and a hydration condition. For example, the correlator 1713may receive heart rate data, skin temperature, bio-impedance data, skinluminosity and hydration level data of a user. In this example, thecorrelator 1713 may determine a correlation between these types ofphysiological data and a dehydration event of the individual. Forexample, the physiological data could be from optical spectroscopy (skinluminosity) and/or bio-impedance data. The correlator 1713 may thendetermine that as the bio-impedance of an individual increases and skinluminosity decreases, a probability of a dehydration event occurringincreases.

Additionally, or alternatively, the correlator 1713 may filter out acorrelation determination (e.g., a determination that data points ordata sets and a hydration condition may be correlated) when acorrelation level is below a threshold level. For example, when thecorrelator 1713 determines that there may be a 30 percent correlationbetween a skin temperature or a bio-impedance level of an individual anda fall event, the correlator 1713 may filter out or disregard thecorrelation information when determining a cause of the fall event. Inanother example, the correlator 1713 can use a learning algorithm ormachine learning to determine when to filter out a correlationdetermination. For example, at a first instance of a fall, there may bea 30 percent correlation between a skin temperature or a bio-impedancelevel of an individual and a fall event The correlator 1713 can monitormultiple fall events and use machine learning to determine that theinitial 30 percent correlation is actually a 60 percent correlation andadjust the filter to not filter out the correlation between the skintemperature or the bio-impedance level of an individual and a fall eventor assign the correlation of the skin temperature or the bio-impedancelevel of an individual and a fall event a different weight.

Additionally, or alternatively, the correlator 1713 may filter out thecorrelation determination based on a schedule of an individual. Forexample, when the correlator 1713 determines that an individual istaking a lunch break, off of work, or sleeping, the correlator 1713 mayfilter out environmental conditions that are associated with theoccupation of the user, e.g., the correlator 1713 can filter out falsepositives.

Additionally, or alternatively, the correlator 1713 may discount orweight a correlation determination based on the correlation level of thecorrelation determination. For example, when the correlator 1713determines that there may only be a 30 percent correlation between anoccupation of an individual and a hydration level of an individual, thecorrelator 1713 may discount or assign a lower weight to the correlationdetermination (relative to a higher correlation percentage such as 90percent) when determining a change in hydration condition.

Additionally, or alternatively, the correlator 1713 may assign weightsto different factors, such as: physiological data 1724 (e.g., differenttypes or qualities of physiological parameters), environmental data 1726(e.g., different types or quality of environmental parameters),Newtonian data 1728 (e.g., different types or quality of Newtonianparameters), profile data 1730, location data 1732 (e.g., differenttypes or quality of location parameters), a time of day, and so forth.In one example, the correlator 1713 may assign a first weight tohydration level data of an individual and a second weight to profiledata of an individual when determining a probability of a change inhydration condition for an individual. In this example, when determiningthe probability of a change in a hydration condition, the correlator1713 may assign a higher weight to the hydration level data relative tothe profile data, for example.

The correlator 1713 may additionally, or alternatively, usepredetermined weights for the physiological data 1724, environmentaldata 1726, Newtonian data 1728, profile data 1730, and location data1732. In another example, the correlator 1713 may receive user definedor predefined weights from an input device indicating the weights forthe different physiological and/or environmental data. In anotherexample, the correlator 1713 may determine the weights to assign to thephysiological data 1724, environmental data 1726, Newtonian data 1728,profile data 1730, and location data 1732 based on correlation levels ofthe physiological data 1024, environmental data 1726, Newtonian data1728, profile data 1730, and location data 1732. For example, when acorrelation level between a hydration condition and a heart rate of anindividual may be relatively low over a threshold period of time and/orunder a threshold number of different conditions, the correlator 1713may assign a low weight to heart rate data when determining a cause of achange in hydration condition.

In one example, the correlator 1713 may assign different weights to oneor more of the physiological data 1724, environmental data 1726,Newtonian data 1728, profile data 1730, and location data 1732 based onother physiological data 1724, environmental data 1726, Newtonian data1728, profile data 1730, and location data 1732. For example, based on alocation of an individual, the correlator 1713 may assign a first weightto environmental data 1726 and a second weight to profile data 1730. Inanother example, the correlator 1713 may assign weights to differenthydration conditions.

Additionally, or alternatively, the correlator 1713 may useenvironmental data 1726 or location data 1732 to determine a cause of achange in hydration condition. For example, when a user is located at afitness facility working out, the correlator 1713 may increase a weightfor a physical exertion related a change in a hydration conditionoccurring because of in physical exertion of a user (such as an increasein a heart rate or decrease in a hydration level of a user). In anotherexample, when a user is located at home in bed resting or sleeping, thecorrelator 1713 may correlate a location of the user with the hydrationcondition of the user. In this example, the correlator 1713 maydetermine that a decrease in probability of a change in a hydrationcondition occurring due to an individual being is located in theirbedroom for a threshold period of time (e.g., a safer environment).

In one embodiment, the correlator 1713 can determine a weighting ofmeasurement information or physiological information using medicalevaluation information. In one example, the medical evaluationinformation includes medical evaluation information of the user, such asa medical physical. The medical evaluation information can include:medical history and health history information, such as whether the useris a smoker or a non-smoker; a user's blood pressure information;hereditary diseases information; a user's sexual health information; auser's dietary information, a user's exercise routine information, suchas how often the user exercises; a user's heart or lung examineinformation; and so forth. In one example, the correlator 1713 can usethe medical evaluation information to set initial weight for differentdata types. The correlator can update or adjust the weights for thedifferent data types using machine learning. For example, thephysiological data 1724, environmental data 1726, and Newtonian data1728 is assigned a first set of weights based on the medical evaluationinformation. As the electronic device 1700 uses the sensors to collectthe physiological data 1724, environmental data 1726, and the Newtoniandata 1728, the correlator 1713 can use the physiological data 1724, theenvironmental data 1726, and the Newtonian data 1728 to customize theweighting of the measurement information or physiological information tothe individual. For example, the correlator 1713 can receive medicalevaluation information for the user input device of the electronicdevice 1700 using an input device of the electronic device 1700.

The correlator 1713 may track, sort and/or filter input data. The inputdata may include: user schedule information, such as a daily schedule ofthe user; survey information, such as information received from surveysof individuals; research information, such as clinical researchinformation or academic research information associated with one or morehydration conditions of the electronic device; and so forth.

The correlator 1713 may use location-based tracking and/or schedulinginformation of the user in determining an expected or probable change ina hydration condition. For example, when a user is a member of a sportsteam, the user's schedule may include practice schedule informationand/or game schedule information. In this example, the correlator 1713may use the schedule information to anticipate that the user may beparticipating in physical activity and increase a probability that achange in hydration condition may occur.

The correlator 1713 may use timer information determining an expected orprobable occurrence of a change in a hydration condition. For example,the correlator can monitor how long it may have been since a user took abreak or consumed water. In this example, as the length of time increasebetween a break or water consumption, the probability that a change inhydration condition may occur increases. In another example, thecorrelator can use the timer information to periodically request aresponse from the user. For example, when a change in hydrationcondition has not occur within a threshold amount of time that wouldtrigger a user response, the electronic device can request a userresponse from the user when the threshold amount of time has beenexceeded.

In another example, the correlator 1713 can have a work mode (the useris at work) and a home mode (the user is at home), where a type ofenvironmental condition that the electronic device monitors for and/or aprobability of a change in a hydration condition occurring can increaseor decrease when switching between the work mode and the home mode. Forexample, when the user has a high risk occupation, the correlator 1713can monitor for change in hydration condition related to the high riskoccupation when the correlator is in a work mode and switch tomonitoring for changes in a hydration condition related to low riskactivities when the correlator is in a home mode.

In another example, the correlator 1713 may use the schedulinginformation in correlation with a location of the user to determine anexpected or probable change in a hydration condition. For example, thescheduling information may indicate that the user may be scheduled toattend a lecture at a physical fitness facility and the correlator 1713may adjust the types or probabilities of a change in a hydrationcondition occurring in view of the scheduling information. In thisexample, while the correlator 1713 may typically increasing aprobability of a change in hydration condition occurring for the user inanticipation of physical activity based on the location information(e.g., the physical fitness facility), the correlator 1713 may adjustthe adjust the types or probabilities of a change in a hydrationcondition occurring in view of the scheduling information that the usermay be attending a lecture rather than working out.

Additionally, or alternatively, the correlator 1713 may track and updateactivity levels of users and correlate these levels with hydrationconditions over time. For example, the GPS sensor of the electronicdevice 1700 may indicate that the user usually works out at the gym onMonday, Wednesday and Friday at 7 a.m. and goes on a long bike ride onSaturday, usually starting about 8:30 a.m. Although these activities maynot be available within the scheduling information or data of theelectronic device 1700 (or other tethered device), the correlator 1713may execute machine learning to add to a user's activity data theseevents that normally occur.

The electronic device 1700 may store historical or previous hydrationcondition information of the user. In one example, the correlator 1013may store the historical information on the memory device 1708 of theelectronic device 1700. In another example, the correlator 1713 may usethe communication device 170 (illustrated in FIG. 1), the communicationunit 1070 (illustrated in FIG. 10), or the communication interface 1790to store the hydration condition information on a memory device coupledto or in communication with the electronic device, such as a cloud-basedstorage device or a memory device of another computing device. Inanother example, the correlator 1713 may be part of a cloud-based systemor the other computing device, as will be discussed in more detail withreference to FIGS. 13 and 14.

The correlator 1713 may filter and/or sort hydration conditioninformation. In one example, the correlator 1718 may receive a filter orsort command from the electronic device or an input device to filterand/or sort the hydration information. In another example, the filter orsort command may include filter parameters and/or sort parameters.

In another example, the correlator 1713 may sort and/or filter the inputdata based on a trending of hydration conditions. For example, thecorrelator 1713 may sort hydration conditions that may be trending in anincreasing direction or a decreasing direction and may sort thehydration conditions based on the trending. In this example, differenthydration conditions for a user may be trending in different directions,such as a dehydration events of a user may be increasing in trending andfall events may be stable or stagnant.

In another embodiment, the baseliner 1715 may receive profileinformation from a new user to include any or a combination of gender,age, weight, health, fitness level, and family health histories. Thehealth and fitness levels of the user may be based at least in part onphysiological measurements received from the physiological sensor(s)1702 and the activity data received from the Newtonian sensors 1704. Thebaseliner 1715 may then identify, from a plurality of baseline profilesof other users (e.g., a group of users), a baseline profile that ismost-similar to the user profile based on a correlation between the userprofile information and baseline profile information. The baselineprofiles can include baseline information of a probability of a changein hydration conditions occurring for a user. The user profiles caninclude information of the types of hydration conditions that may beprobable to occur for user.

The baseliner 1715 may then be able to set a baseline against which tojudge a hydration condition. In an alternate embodiment, the baselineprofile that is most-similar to the user profile is identified from anaggregated baseline profile for a plurality of individuals correspondingto the plurality of baseline profiles. Alternatively, or additionally,the most-similar profiles may look at a hydration condition that occursfor the individual as compared to a group. For example, the user may bemost similar to another individual because they both reactphysiologically similarly to hot temperatures outside. In anotherexample, the user may have a similar dehydration profile to themost-similar profile, meaning, when the user works out the user mayreach a dehydration level at a certain point in time that substantiallymatches the timing of the most-similar profile.

The electronic device 1700 may further receive survey information and/orresearch information from an input device with which to build or add tothe user and/or baseline profiles. For example, the electronic device1700 may receive survey information that includes: gender information,age information, physical weight information, general healthinformation, family information, fitness level information, and soforth. In one example, the correlator 1713 may determine a correlationbetween the survey information and user input data. For example, thecorrelator 1713 may correlate the age, weight, fitness level, andgeneral health level of a user with survey information from otherindividuals to determine a correlation between the survey informationfor the individual and the other individuals. In this example, thebaseliner 1715 may set a baseline for a measurement of the electronicdevice 1700 for the individual based on baselines for the otherindividuals with the same or similar survey information.

In another example, the correlator 1713 may correlate the userinformation with research information (such as research papers, clinicalstudies, and so forth). For example, the electronic device may retrieveresearch information related to a physiological parameter, thecorrelator 1713 may then correlate the research information withhydration conditions for the user to generate a research correlation.The baseliner 1715 may then adjust the baseline set for the user relatedto the hydration conditions in response to the research correlation.

The correlator 1713 can store hydration condition information in ahydration condition database 1712. In one embodiment, the correlator1713 can determine parameters associated with hydration conditions. Theparameters can include threshold values for measurements or data values,such as physiological sensor measurements, environmental sensormeasurements, Newtonian sensor measurements, location sensormeasurements, or profile data 1730. The correlator 1713 can store thehydration condition and the associated hydration parameters in thehydration condition database 1712. For example, the correlator 1713 candetermine that parameters for a heat stroke event can be a skintemperature above a 100 degree temperature, blood pressure above 150systolic, and a bio-impedance level above 15000 ohms (e.g., adehydration level threshold). In this example, the correlator 1713 candetermine these parameters and can store the hydration condition withthe associated parameters in the hydration condition database 1712. Inanother example, the store predetermined hydration conditions with theassociated parameters. In another example, the hydration conditiondatabase 1712 can receive the hydration conditions and the associatedparameters from another device or server 1794.

The preceding examples are intended for purposes of illustration and arenot intended to be limiting. The correlator 1713 may identify acorrelation between various data points, data sets, data types, and/orhydration conditions. After having a correlation that informs, forexample, a heat stroke event, the hydration level, and/or oxygenationlevel of the user, and further in consideration of a present activitylevel of the user, the alerter 1717 may alert the user at the propertime when to hydrate or how to moderate activity levels to avoid orminimize a dehydrated condition.

FIG. 18 provides an example illustration of a processing devicedisclosed herein, such as a user equipment (UE), a base station, anelectronic device (UMD), a mobile wireless device, a mobilecommunication device, a tablet, a handset, or other type of wirelessdevice according to one embodiment. The device may include one or moreantennas 1890 configured to communicate with a node or transmissionstation, such as a base station (BS), an evolved Node B (eNode B), abaseband unit (BBU), a remote radio head (RRH), a remote radio equipment(RRE), a relay station (RS), a radio equipment (RE), a remote radio unit(RRU), a central processing module (CPM), or other type of wireless widearea network (WWAN) access point. The device may be configured tocommunicate using at least one wireless communication standard including3GPP LTE, WiMAX, High Speed Packet Access (HSPA), Bluetooth, and Wi-Fi.The device may communicate using separate antennas for each wirelesscommunication standard or shared antennas for multiple wirelesscommunication standards. The device may communicate in a wireless localarea network (WLAN), a wireless personal area network (WPAN), and/or aWWAN.

FIG. 18 also provides an illustration of a microphone 1810 and one ormore speakers 1820 that may be used for audio input and output from thedevice. The display screen 1830 may be a liquid crystal display (LCD)screen, or other type of display screen such as an organic lightemitting diode (OLED) display. The display screen 1830 may be configuredas a touch screen. The touch screen may use capacitive, resistive, oranother type of touch screen technology. An application processor 1840and a graphics processor 1850 may be coupled to internal memory 1860 toprovide processing and display capabilities. A non-volatile memory portmay also be used to provide data input/output options to a user. Thenon-volatile memory port 1870 may also be used to expand the memorycapabilities of the wireless device. A keyboard 1880 may be integratedwith the wireless device or wirelessly connected to the wireless deviceto provide additional user input. A virtual keyboard may also beprovided using the touch screen.

Various techniques, or certain aspects or portions thereof, may take theform of program code (i.e., instructions) embodied in tangible media,such as floppy diskettes, CD-ROMs, hard drives, non-transitory computerreadable storage medium, or any other machine-readable storage mediumwhere, when the program code is loaded into and executed by a machine,such as a computer, the machine becomes an apparatus for practicing thevarious techniques. In the case of program code execution onprogrammable computers, the computing device may include a processor, astorage medium readable by the processor (including volatile andnon-volatile memory and/or storage elements), at least one input device,and at least one output device. The volatile and non-volatile memoryand/or storage elements may be a RAM, EPROM, flash drive, optical drive,magnetic hard drive, or other medium for storing electronic data. Thebase station and mobile station may also include a transceiver module, acounter module, a processing module, and/or a clock module or timermodule. One or more programs that may implement or utilize the varioustechniques described herein may use an application programming interface(API), reusable controls, and the like. Such programs may be implementedin a high level procedural or object oriented programming language tocommunicate with a computer system. However, the program(s) may beimplemented in assembly or machine language, if desired. In any case,the language may be a compiled or interpreted language, and combinedwith hardware implementations.

It should be understood that many of the functional units described inthis specification have been labeled as modules, in order to moreparticularly emphasize their implementation independence. For example, amodule may be implemented as a hardware circuit comprising custom VLSIcircuits or gate arrays, off-the-shelf semiconductors such as logicchips, transistors, or other discrete components. A module may also beimplemented in programmable hardware devices such as field programmablegate arrays, programmable array logic, programmable logic devices or thelike.

Modules may also be implemented in software for execution by varioustypes of processors. An identified module of executable code may, forinstance, include one or more physical or logical blocks of computerinstructions, which may, for instance, be organized as an object,procedure, or function. Nevertheless, the executables of an identifiedmodule need not be physically located together, but may includedisparate instructions stored in different locations which, when joinedlogically together, include the module and achieve the stated purposefor the module.

Indeed, a module of executable code may be a single instruction, or manyinstructions, and may even be distributed over several different codesegments, among different programs, and across several memory devices.Similarly, operational data may be identified and illustrated hereinwithin modules, and may be embodied in any suitable form and organizedwithin any suitable type of data structure. The operational data may becollected as a single data set, or may be distributed over differentlocations including over different storage devices, and may exist, atleast partially, merely as electronic signals on a system or network.The modules may be passive or active, including agents operable toperform desired functions.

Reference throughout this specification to “an example” means that aparticular feature, structure, or characteristic described in connectionwith the example is included in at least one embodiment of the presentdisclosure. Thus, appearances of the phrases “in an example” in variousplaces throughout this specification are not necessarily all referringto the same embodiment.

As used herein, a plurality of items, structural elements, compositionalelements, and/or materials may be presented in a common list forconvenience. However, these lists should be construed as though eachmember of the list is individually identified as a separate and uniquemember. Thus, no individual member of such list should be construed as ade facto equivalent of any other member of the same list solely based ontheir presentation in a common group without indications to thecontrary. In addition, various embodiments and example of the presentdisclosure may be referred to herein along with alternatives for thevarious components thereof. It is understood that such embodiments,examples, and alternatives are not to be construed as defactoequivalents of one another, but are to be considered as separate andautonomous representations of the present disclosure.

Furthermore, the described features, structures, or characteristics maybe combined in any suitable manner in one or more embodiments. In theforegoing description, numerous specific details are provided, such asexamples of layouts, distances, network examples, etc., to provide athorough understanding of embodiments of the disclosure. One skilled inthe relevant art will recognize, however, that the disclosure may bepracticed without one or more of the specific details, or with othermethods, components, layouts, etc. In other instances, well-knownstructures, materials, or operations are not shown or described indetail to avoid obscuring aspects of the disclosure.

While the foregoing examples are illustrative of the principles of thepresent disclosure in one or more particular applications, it will beapparent to those of ordinary skill in the art that numerousmodifications in form, usage and details of implementation may be madewithout the exercise of inventive faculty, and without departing fromthe principles and concepts of the disclosure. Accordingly, it is notintended that the disclosure be limited, except as by the claims setforth below.

Turning to FIG. 19 a block diagram of an exemplary computer systemformed with a processor that includes execution units to execute aninstruction, where one or more of the interconnects implement one ormore features in accordance with one example implementation of thepresent disclosure is illustrated. System 1900 includes a component,such as a processor 1902 to employ execution units including logic toperform algorithms for process data, in accordance with the presentdisclosure, such as in the example implementation described herein.System 1900 is representative of processing systems based on the PENTIUMIII™, PENTIUM 4™, XEON™, Itanium, XSCALE™ and/or SRONGARM™microprocessors available from Intel Corporation of Santa Clara, Calif.,although other systems (including PCs having other microprocessors,engineering workstations, set-top boxes and the like) may also be used.In one example implementation, sample system 1900 executes a version ofthe WINDOWS™ operating system available from Microsoft Corporation ofRedmond, Wash., although other operating systems (UNIX and Linux forexample), embedded software, and/or graphical user interfaces, may alsobe used. Thus, example implementations of the present disclosure are notlimited to any specific combination of hardware circuitry and software.

Example implementations are not limited to computer systems. Alternativeexample implementations of the present disclosure can be used in otherdevices such as handheld devices and embedded applications. Someexamples of handheld devices include cellular phones, Internet Protocoldevices, digital cameras, personal digital assistants (PDAs), andhandheld PCs. Embedded applications can include a micro controller, adigital signal processor (DSP), system on a chip, network computers(NetPC), set-top boxes, network hubs, wide area network (WAN) switches,or any other system that can perform one or more instructions inaccordance with at least one example implementation.

Alternative example implementations of the present disclosure can beused in other devices, such as an electronic device. The electronicdevice may be connected (e.g., networked) to other machines in a LAN, anintranet, an extranet, or the Internet. The electronic device mayoperate in the capacity of a server or a client device in aclient-server network environment, or as a peer device in a peer-to-peer(or distributed) network environment. The electronic device may be apersonal computer (PC), a tablet PC, a set-top box (STB), a cellulartelephone, a smartphone, a web appliance, a server, a network router,switch or bridge, or any electronic device capable of executing a set ofinstructions (sequential or otherwise) that specify actions to be takenby that electronic device. Further, while only a single electronicdevice is illustrated, the term “electronic device” shall also be takento include any collection of electronic devices that individually orjointly execute a set (or multiple sets) of instructions to perform anyone or more of the methodologies discussed herein.

The system 1900 may correspond to the processing device 425 (illustratedin FIG. 4), the controller 1080 (illustrated in FIG. 10), the processingdevice 804 (illustrated in FIG. 8), or the processor 1703 (illustratedin FIG. 17). The system 1900 may correspond to at least a portion of acloud-based computer system.

In this illustrated example implementation, processor 1902 includes oneor more execution units 1908 to implement an algorithm that is toperform at least one instruction. One example implementation may bedescribed in the context of a single processor desktop or server system,but alternative example implementations may be included in amultiprocessor system. System 1900 is an example of a ‘hub’ systemarchitecture. The computer system 1900 includes a processor 1902 toprocess data signals. The processor 1902, as one illustrative example,includes a complex instruction set computer (CISC) microprocessor, areduced instruction set computing (RISC) microprocessor, a very longinstruction word (VLIW) microprocessor, a processor implementing acombination of instruction sets, or any other processor device, such asa digital signal processor, for example. The processor 1902 is coupledto a processor bus 1910 that transmits data signals between theprocessor 1902 and other components in the system 1900. The elements ofsystem 1900 (e.g. graphics accelerator 1912, memory controller hub 1916,memory 1920, I/O controller hub 1924, wireless transceiver 1926, FlashBIOS 1928, Network controller 1934, Audio controller 1936, Serialexpansion port 1938, I/O controller 1940, etc.) perform theirconventional functions that are well known to those familiar with theart.

In one example implementation, the processor 1902 includes a Level 1(L1) internal cache memory 1904. Depending on the architecture, theprocessor 1902 may have a single internal cache or multiple levels ofinternal caches. Other example implementations include a combination ofboth internal and external caches depending on the particularimplementation and needs. Register file 1906 is to store different typesof data in various registers including integer registers, floating pointregisters, vector registers, banked registers, shadow registers,checkpoint registers, status registers, and instruction pointerregister.

Execution unit 1908, including logic to perform integer and floatingpoint operations, also resides in the processor 1902. The processor1902, in one example implementation, includes a microcode (ucode) ROM tostore microcode, which when executed, is to perform algorithms forcertain macroinstructions or handle complex scenarios. Here, microcodeis potentially updateable to handle logic bugs/fixes for processor 1902.For one example implementation, execution unit 1908 includes logic tohandle a packed instruction set 1909. By including the packedinstruction set 1909 in the instruction set of a general-purposeprocessor 1902, along with associated circuitry to execute theinstructions, the operations used by many multimedia applications may beperformed using packed data in a general-purpose processor 1902. Thus,many multimedia applications are accelerated and executed moreefficiently by using the full width of a processor's data bus forperforming operations on packed data. This potentially eliminates theneed to transfer smaller units of data across the processor's data busto perform one or more operations, one data element at a time.

Alternate example implementations of an execution unit 1908 may also beused in micro controllers, embedded processors, graphics devices, DSPs,and other types of logic circuits. System 1900 includes a memory 1920.Memory 1920 includes a dynamic random access memory (DRAM) device, astatic random access memory (SRAM) device, flash memory device, or othermemory device. Memory 1920 stores instructions and/or data representedby data signals that are to be executed by the processor 1902.

A system logic chip 1916 is coupled to the processor bus 1910 and memory1920. The system logic chip 1916 in the illustrated exampleimplementation is a memory controller hub (MCH). The processor 1902 cancommunicate to the MCH 1916 via a processor bus 1910. The MCH 1916provides a high bandwidth memory path 1918 to memory 1920 forinstruction and data storage and for storage of graphics commands, dataand textures. The MCH 1916 is to direct data signals between theprocessor 1902, memory 1920, and other components in the electronicdevice 1300 and to bridge the data signals between processor bus 1910,memory 1920, and system I/O 1922. In some example implementations, thesystem logic chip 1916 can provide a graphics port for coupling to agraphics controller 1912. The MCH 1916 is coupled to memory 1920 througha memory interface 1918. The graphics card 1912 is coupled to the MCH1916 through an Accelerated Graphics Port (AGP) interconnect 1914.

System 1900 uses a proprietary hub interface bus 1922 to couple the MCH1316 to the I/O controller hub (ICH) 1930. The ICH 1930 provides directconnections to some I/O devices via a local I/O bus. The local I/O busis a high-speed I/O bus for connecting peripherals to the memory 1920,chipset, and processor 1902. Some examples are the audio controller,firmware hub (flash BIOS) 1928, wireless transceiver 1926, data storage1924, legacy I/O controller containing user input and keyboardinterfaces, a serial expansion port such as Universal Serial Bus (USB),and a network controller 1934. The data storage device 1924 can includea hard disk drive, a floppy disk drive, a CD-ROM device, a flash memorydevice, or other mass storage device.

For another example implementation of a system, an instruction inaccordance with one example implementation can be used with a system ona chip. One example implementation of a system on a chip includes of aprocessor and a memory. The memory for one such system is a flashmemory. The flash memory can be located on the same die as the processorand other system components. Additionally, other logic blocks such as amemory controller or graphics controller can also be located on a systemon a chip.

In the following description, numerous specific details are set forth,such as examples of specific types of processors and systemconfigurations, specific hardware structures, specific architectural andmicro architectural details, specific register configurations, specificinstruction types, specific system components, specificmeasurements/heights, specific processor pipeline stages and operationetc. in order to provide a thorough understanding of the presentdisclosure. It will be apparent, however, to one skilled in the art thatthese specific details need not be employed to practice the presentdisclosure. In other instances, well known components or methods, suchas specific and alternative processor architectures, specific logiccircuits/code for described algorithms, specific firmware code, specificinterconnect operation, specific logic configurations, specificmanufacturing techniques and materials, specific compilerimplementations, specific expression of algorithms in code, specificpower down and gating techniques/logic and other specific operationaldetails of computer system haven't been described in detail in order toavoid unnecessarily obscuring the present disclosure.

Although the following example implementations may be described withreference to energy conservation and energy efficiency in specificintegrated circuits, such as in computing platforms or microprocessors,other example implementations are applicable to other types ofintegrated circuits and logic devices. Similar techniques and teachingsof example implementations described herein may be applied to othertypes of circuits or semiconductor devices that may also benefit frombetter energy efficiency and energy conservation. For example, thedisclosed example implementations are not limited to desktop computersystems or Ultrabooks™. And may be also used in other devices, such ashandheld devices, tablets, other thin notebooks, systems on a chip (SOC)devices, and embedded applications. Some examples of handheld devicesinclude cellular phones, Internet protocol devices, digital cameras,personal digital assistants (PDAs), and handheld PCs. Embeddedapplications typically include a microcontroller, a digital signalprocessor (DSP), a system on a chip, network computers (NetPC), set-topboxes, network hubs, wide area network (WAN) switches, or any othersystem that can perform the functions and operations taught below.Moreover, the apparatus', methods, and systems described herein are notlimited to physical computing devices, but may also relate to softwareoptimizations for energy conservation and efficiency. As will becomereadily apparent in the description below, the example implementationsof methods, apparatus', and systems described herein (whether inreference to hardware, firmware, software, or a combination thereof) arevital to a ‘green technology’ future balanced with performanceconsiderations.

It is described that the system may be any kind of computer or embeddedsystem. The disclosed embodiments may especially be used for electronicdevice, electronic implants, sensory and control infrastructure devices,controllers, supervisory control and data acquisition (SCADA) systems,or the like. Moreover, the apparatuses, methods, and systems describedherein are not limited to physical computing devices, but may alsorelate to software optimizations for energy conservation and efficiency.As will become readily apparent in the description below, theembodiments of methods, apparatuses, and systems described herein(whether in reference to hardware, firmware, software, or a combinationthereof).

Although the following example implementations are described withreference to a processor, other example implementations are applicableto other types of integrated circuits and logic devices. Similartechniques and teachings of example implementations of the presentdisclosure can be applied to other types of circuits or semiconductordevices that can benefit from higher pipeline throughput and improvedperformance. The teachings of example implementations of the presentdisclosure are applicable to any processor or machine that performs datamanipulations. However, the present disclosure is not limited toprocessors or machines that perform 512 bit, 256 bit, 128 bit, 64 bit,32 bit, or 16 bit data operations and can be applied to any processorand machine in which manipulation or management of data is performed. Inaddition, the following description provides examples, and theaccompanying drawings show various examples for the purposes ofillustration. However, these examples should not be construed in alimiting sense as they are merely intended to provide examples ofexample implementations of the present disclosure rather than to providean exhaustive list of all possible implementations of exampleimplementations of the present disclosure.

Although the below examples describe instruction handling anddistribution in the context of execution units and logic circuits, otherexample implementations of the present disclosure can be accomplished byway of a data or instructions stored on a machine-readable, tangiblemedium, which when performed by a machine cause the machine to performfunctions consistent with at least one example implementation of thepresent disclosure. In one example implementation, functions associatedwith example implementations of the present disclosure are embodied inmachine-executable instructions. The instructions can be used to cause ageneral-purpose or special-purpose processor that is programmed with theinstructions to perform the steps of the present disclosure. Exampleimplementations of the present disclosure may be provided as a computerprogram product or software which may include a machine orcomputer-readable medium having stored thereon instructions which may beused to program a computer (or other electronic devices) to perform oneor more operations according to example implementations of the presentdisclosure. Alternatively, steps of example implementations of thepresent disclosure might be performed by specific hardware componentsthat contain fixed-function logic for performing the steps, or by anycombination of programmed computer components and fixed-functionhardware components.

Instructions used to program logic to perform example implementations ofthe present disclosure can be stored within a memory in the system, suchas DRAM, cache, flash memory, or other storage. Furthermore, theinstructions can be distributed via a network or by way of othercomputer readable media. Thus a machine-readable medium may include anymechanism for storing or transmitting information in a form readable bya machine (e.g., a computer), but is not limited to, floppy diskettes,optical disks, Compact Disc, Read-Only Memory (CD-ROMs), andmagneto-optical disks, Read-Only Memory (ROMs), Random Access Memory(RAM), Erasable Programmable Read-Only Memory (EPROM), ElectricallyErasable Programmable Read-Only Memory (EEPROM), magnetic or opticalcards, flash memory, or a tangible, machine-readable storage used in thetransmission of information over the Internet via electrical, optical,acoustical or other forms of propagated signals (e.g., carrier waves,infrared signals, digital signals, etc.). Accordingly, thecomputer-readable medium includes any type of tangible machine-readablemedium suitable for storing or transmitting electronic instructions orinformation in a form readable by a machine (e.g., a computer).

The embodiments of methods, hardware, software, firmware or code setforth above may be implemented via instructions or code stored on amachine-accessible, machine readable, computer accessible, or computerreadable medium which are executable by a processing element. Anon-transitory machine-accessible/readable medium includes any mechanismthat provides (i.e., stores and/or transmits) information in a formreadable by a machine, such as a computer or electronic system. Forexample, a non-transitory machine-accessible medium includesrandom-access memory (RAM), such as static RAM (SRAM) or dynamic RAM(DRAM); ROM; magnetic or optical storage medium; flash memory devices;electrical storage devices; optical storage devices; acoustical storagedevices; other form of storage devices for holding information receivedfrom transitory (propagated) signals (e.g., carrier waves, infraredsignals, digital signals); etc., which are to be distinguished from thenon-transitory mediums that may receive information there from.

Instructions used to program logic to perform embodiments of thedisclosure may be stored within a memory in the system, such as DRAM,cache, flash memory, or other storage. Furthermore, the instructions maybe distributed via a network or by way of other computer readable media.Thus a machine-readable medium may include any mechanism for storing ortransmitting information in a form readable by a machine (e.g., acomputer), but is not limited to, floppy diskettes, optical disks,Compact Disc, Read-Only Memory (CD-ROMs), and magneto-optical disks,Read-Only Memory (ROMs), Random Access Memory (RAM), ErasableProgrammable Read-Only Memory (EPROM), Electrically ErasableProgrammable Read-Only Memory (EEPROM), magnetic or optical cards, flashmemory, or a tangible, machine-readable storage used in the transmissionof information over the Internet via electrical, optical, acoustical orother forms of propagated signals (e.g., carrier waves, infraredsignals, digital signals, etc.). Accordingly, the computer-readablemedium includes any type of tangible machine-readable medium suitablefor storing or transmitting electronic instructions or information in aform readable by a machine (e.g., a computer)

The computer-readable storage medium may also be used to storeinstructions utilizing logic and/or a software library containingmethods that call the above applications. While the computer-readablestorage medium can be a single medium, the term “computer-readablestorage medium” should be taken to include a single medium or multiplemedia (e.g., a centralized or distributed database, and/or associatedcaches and servers) that store the one or more sets of instructions. Theterm “computer-readable storage medium” shall accordingly be taken toinclude, but not be limited to, solid-state memories, optical media, andmagnetic media.

A design may go through various stages, from creation to simulation tofabrication. Data representing a design may represent the design in anumber of manners. First, as is useful in simulations, the hardware maybe represented using a hardware description language or anotherfunctional description language. Additionally, a circuit level modelwith logic and/or transistor gates may be produced at some stages of thedesign process. Furthermore, most designs, at some stage, reach a levelof data representing the physical placement of various devices in thehardware model. In the case where conventional semiconductor fabricationtechniques are used, the data representing the hardware model may be thedata specifying the presence or absence of various features on differentmask layers for masks used to produce the integrated circuit. In anyrepresentation of the design, the data may be stored in any form of amachine readable medium. A memory or a magnetic or optical storage suchas a disc may be the machine readable medium to store informationtransmitted via optical or electrical wave modulated or otherwisegenerated to transmit such information. When an electrical carrier waveindicating or carrying the code or design is transmitted, to the extentthat copying, buffering, or re-transmission of the electrical signal isperformed, a new copy is made. Thus, a communication provider or anetwork provider may store on a tangible, machine-readable medium, atleast temporarily, an article, such as information encoded into acarrier wave, embodying techniques of example implementations of thepresent disclosure.

In modern processors, a number of different execution units are used toprocess and execute a variety of code and instructions. Not allinstructions are created equal as some are quicker to complete whileothers can take a number of clock cycles to complete. The faster thethroughput of instructions, the better the overall performance of theprocessor. Thus it would be advantageous to have as many instructionsexecute as fast as possible. However, there are certain instructionsthat have greater complexity and require more in terms of execution timeand processor resources. For example, there are floating pointinstructions, load/store operations, data moves, etc.

As more computer systems are used in internet, text, and multimediaapplications, additional processor support has been introduced overtime. In one example implementation, an instruction set may beassociated with one or more computer architectures, including datatypes, instructions, register architecture, addressing modes, memoryarchitecture, interrupt and exception handling, and external input andoutput (I/O).

In one example implementation, the instruction set architecture (ISA)may be implemented by one or more micro-architectures, which includesprocessor logic and circuits used to implement one or more instructionsets. Accordingly, processors with different micro-architectures canshare at least a portion of a common instruction set. For example,Intel® Pentium 4 processors, Intel® Core™ processors, and processorsfrom Advanced Micro Devices, Inc. of Sunnyvale Calif. implement nearlyidentical versions of the x86 instruction set (with some extensions thathave been added with newer versions), but have different internaldesigns. Similarly, processors designed by other processor developmentcompanies, such as ARM Holdings, Ltd., MIPS, or their licensees oradopters, may share at least a portion a common instruction set, but mayinclude different processor designs. For example, the same registerarchitecture of the ISA may be implemented in different ways indifferent micro-architectures using new or well-known techniques,including dedicated physical registers, one or more dynamicallyallocated physical registers using a register renaming mechanism (e.g.,the use of a Register Alias Table (RAT), a Reorder Buffer (ROB) and aretirement register file. In one example implementation, registers mayinclude one or more registers, register architectures, register files,or other register sets that may or may not be addressable by a softwareprogrammer.

In one example implementation, an instruction may include one or moreinstruction formats. In one example implementation, an instructionformat may indicate various fields (number of bits, location of bits,etc.) to specify, among other things, the operation to be performed andthe operand(s) on which that operation is to be performed. Someinstruction formats may be further broken defined by instructiontemplates (or sub formats). For example, the instruction templates of agiven instruction format may be defined to have different subsets of theinstruction format's fields and/or defined to have a given fieldinterpreted differently. In one example implementation, an instructionis expressed using an instruction format (and, if defined, in a givenone of the instruction templates of that instruction format) andspecifies or indicates the operation and the operands upon which theoperation will operate.

Scientific, financial, auto-vectorized general purpose, RMS(recognition, mining, and synthesis), and visual and multimediaapplications (e.g., 2D/3D graphics, image processing, videocompression/decompression, voice recognition algorithms and audiomanipulation) may require the same operation to be performed on a largenumber of data items. In one example implementation, Single InstructionMultiple Data (SIMD) refers to a type of instruction that causes aprocessor to perform an operation on multiple data elements. SIMDtechnology may be used in processors that can logically divide the bitsin a register into a number of fixed-sized or variable-sized dataelements, each of which represents a separate value. For example, in oneexample implementation, the bits in a 64-bit register may be organizedas a source operand containing four separate 16-bit data elements, eachof which represents a separate 16-bit value. This type of data may bereferred to as ‘packed’ data type or ‘vector’ data type, and operands ofthis data type are referred to as packed data operands or vectoroperands. In one example implementation, a packed data item or vectormay be a sequence of packed data elements stored within a singleregister, and a packed data operand or a vector operand may a source ordestination operand of a SIMD instruction (or ‘packed data instruction’or a ‘vector instruction’). In one example implementation, a SIMDinstruction specifies a single vector operation to be performed on twosource vector operands to generate a destination vector operand (alsoreferred to as a result vector operand) of the same or different size,with the same or different number of data elements, and in the same ordifferent data element order.

SIMD technology, such as that employed by the Intel® Core™ processorshaving an instruction set including x86, MMX™, Streaming SIMD Extensions(SSE), SSE2, SSE3, SSE4.1, and SSE4.2 instructions, ARM processors, suchas the ARM Cortex® family of processors having an instruction setincluding the Vector Floating Point (VFP) and/or NEON instructions, andMIPS processors, such as the Loongson family of processors developed bythe Institute of Computing Technology (ICT) of the Chinese Academy ofSciences, has enabled a significant improvement in applicationperformance (Core™ and MMX™ are registered trademarks or trademarks ofIntel Corporation of Santa Clara, Calif.).

In one example implementation, destination and source registers/data aregeneric terms to represent the source and destination of thecorresponding data or operation. In some example implementations, theymay be implemented by registers, memory, or other storage areas havingother names or functions than those depicted. For example, in oneexample implementation, “DEST1” may be a temporary storage register orother storage area, whereas “SRC1” and “SRC2” may be a first and secondsource storage register or other storage area, and so forth. In otherexample implementations, two or more of the SRC and DEST storage areasmay correspond to different data storage elements within the samestorage area (e.g., a SIMD register). In one example implementation, oneof the source registers may also act as a destination register by, forexample, writing back the result of an operation performed on the firstand second source data to one of the two source registers serving as adestination registers.

A design may go through various stages, from creation to simulation tofabrication. Data representing a design may represent the design in anumber of manners. First, as is useful in simulations, the hardware maybe represented using a hardware description language or anotherfunctional description language. Additionally, a circuit level modelwith logic and/or transistor gates may be produced at some stages of thedesign process. Furthermore, most designs, at some stage, reach a levelof data representing the physical placement of various devices in thehardware model. In the case where conventional semiconductor fabricationtechniques are used, the data representing the hardware model may be thedata specifying the presence or absence of various features on differentmask layers for masks used to produce the integrated circuit. In anyrepresentation of the design, the data may be stored in any form of amachine readable medium. A memory or a magnetic or optical storage suchas a disc may be the machine readable medium to store informationtransmitted via optical or electrical wave modulated or otherwisegenerated to transmit such information. When an electrical carrier waveindicating or carrying the code or design is transmitted, to the extentthat copying, buffering, or re-transmission of the electrical signal isperformed, a new copy is made. Thus, a communication provider or anetwork provider may store on a tangible, machine-readable medium, atleast temporarily, an article, such as information encoded into acarrier wave, embodying techniques of embodiments of the presentdisclosure.

A module as used herein refers to any combination of hardware, software,and/or firmware. As an example, a module includes hardware, such as amicro-controller, associated with a non-transitory medium to store codeadapted to be executed by the micro-controller. Therefore, reference toa module, in one embodiment, refers to the hardware, which isspecifically configured to recognize and/or execute the code to be heldon a non-transitory medium. Furthermore, in another embodiment, use of amodule refers to the non-transitory medium including the code, which isspecifically adapted to be executed by the microcontroller to performpredetermined operations. And as may be inferred, in yet anotherembodiment, the term module (in this example) may refer to thecombination of the microcontroller and the non-transitory medium. Oftenmodule boundaries that are illustrated as separate commonly vary andpotentially overlap. For example, a first and a second module may sharehardware, software, firmware, or a combination thereof, whilepotentially retaining some independent hardware, software, or firmware.In one embodiment, use of the term logic includes hardware, such astransistors, registers, or other hardware, such as programmable logicdevices.

Use of the phrase ‘configured to,’ in one embodiment, refers toarranging, putting together, manufacturing, offering to sell, importingand/or designing an apparatus, hardware, logic, or element to perform adesignated or determined task. In this example, an apparatus or elementthereof that is not operating is still ‘configured to’ perform adesignated task if it is designed, coupled, and/or interconnected toperform said designated task. As a purely illustrative example, a logicgate may provide a 0 or a 1 during operation. But a logic gate‘configured to’ provide an enable signal to a clock does not includeevery potential logic gate that may provide a 1 or 0. Instead, the logicgate is one coupled in some manner that during operation the 1 or 0output is to enable the clock. Note once again that use of the term‘configured to’ does not require operation, but instead focus on thelatent state of an apparatus, hardware, and/or element, where in thelatent state the apparatus, hardware, and/or element is designed toperform a particular task when the apparatus, hardware, and/or elementis operating.

Furthermore, use of the phrases ‘to,’ ‘capable of/to,’ and or ‘operableto,’ in one embodiment, refers to some apparatus, logic, hardware,and/or element designed in such a way to enable use of the apparatus,logic, hardware, and/or element in a specified manner. Note as abovethat use of to, capable to, or operable to, in one embodiment, refers tothe latent state of an apparatus, logic, hardware, and/or element, wherethe apparatus, logic, hardware, and/or element is not operating but isdesigned in such a manner to enable use of an apparatus in a specifiedmanner.

A value, as used herein, includes any known representation of a number,a state, a logical state, or a binary logical state. Often, the use oflogic levels, logic values, or logical values is also referred to as 1'sand 0's, which simply represents binary logic states. For example, a 1refers to a high logic level and 0 refers to a low logic level. In oneembodiment, a storage cell, such as a transistor or flash cell, may becapable of holding a single logical value or multiple logical values.However, other representations of values in computer systems have beenused. For example the decimal number ten may also be represented as abinary value of 1010 and a hexadecimal letter A. Therefore, a valueincludes any representation of information capable of being held in acomputer system.

Moreover, states may be represented by values or portions of values. Asan example, a first value, such as a logical one, may represent adefault or initial state, while a second value, such as a logical zero,may represent a non-default state. In addition, the terms reset and set,in one embodiment, refer to a default and an updated value or state,respectively. For example, a default value potentially includes a highlogical value, i.e. reset, while an updated value potentially includes alow logical value, i.e. set. Note that any combination of values may beutilized to represent any number of states.

Reference throughout this specification to “one embodiment” or “anembodiment” means that a particular feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment of the present disclosure. Thus, theappearances of the phrases “in one embodiment” or “in an embodiment” invarious places throughout this specification are not necessarily allreferring to the same embodiment. Furthermore, the particular features,structures, or characteristics may be combined in any suitable manner inone or more embodiments.

In the foregoing specification, a detailed description has been givenwith reference to specific exemplary embodiments. It will, however, beevident that various modifications and changes may be made theretowithout departing from the broader spirit and scope of the disclosure asset forth in the appended claims. The specification and drawings are,accordingly, to be regarded in an illustrative sense rather than arestrictive sense. Furthermore, the foregoing use of embodiment andother exemplarily language does not necessarily refer to the sameembodiment or the same example, but may refer to different and distinctembodiments, as well as potentially the same embodiment.

Some portions of the detailed description are presented in terms ofalgorithms and symbolic representations of operations on data bitswithin a computer memory. These algorithmic descriptions andrepresentations are the means used by those skilled in the dataprocessing arts to most effectively convey the substance of their workto others skilled in the art. An algorithm is here and generally,conceived to be a self-consistent sequence of operations leading to adesired result. The operations are those requiring physicalmanipulations of physical quantities. Usually, though not necessarily,these quantities take the form of electrical or magnetic signals capableof being stored, transferred, combined, compared and otherwisemanipulated. It has proven convenient at times, principally for reasonsof common usage, to refer to these signals as bits, values, elements,symbols, characters, terms, numbers or the like. The blocks describedherein may be hardware, software, firmware or a combination thereof.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the above discussion, itis appreciated that throughout the description, discussions utilizingterms such as “defining,” “receiving,” “determining,” “issuing,”“linking,” “associating,” “obtaining,” “authenticating,” “prohibiting,”“executing,” “requesting,” “communicating,” or the like, refer to theactions and processes of a computing system, or similar electroniccomputing device, that manipulates and transforms data represented asphysical (e.g., electronic) quantities within the computing system'sregisters and memories into other data similarly represented as physicalquantities within the computing system memories or registers or othersuch information storage, transmission or display devices.

The words “example” or “exemplary” are used herein to mean serving as anexample, instance or illustration. Any aspect or design described hereinas “example” or “exemplary” is not necessarily to be construed aspreferred or advantageous over other aspects or designs. Rather, use ofthe words “example” or “exemplary” is intended to present concepts in aconcrete fashion. As used in this application, the term “or” is intendedto mean an inclusive “or” rather than an exclusive “or.” That is, unlessspecified otherwise, or clear from context, “X includes A or B” isintended to mean any of the natural inclusive permutations. That is, ifX includes A; X includes B; or X includes both A and B, then “X includesA or B” is satisfied under any of the foregoing instances. In addition,the articles “a” and “an” as used in this application and the appendedclaims should generally be construed to mean “one or more” unlessspecified otherwise or clear from context to be directed to a singularform. Moreover, use of the term “an embodiment” or “one embodiment” or“an implementation” or “one implementation” throughout is not intendedto mean the same embodiment or implementation unless described as such.Also, the terms “first,” “second,” “third,” “fourth,” etc. as usedherein are meant as labels to distinguish among different elements andmay not necessarily have an ordinal meaning according to their numericaldesignation.

What is claimed is:
 1. An electronic device comprising: a housing havingan outer surface shaped to affix to a body of a user, wherein thehousing comprises a first cavity, a second cavity, and a third cavity; afirst light source embedded within the first cavity at a first position;wherein the first light source is operable to emit a first light intothe body at a first wavelength of light corresponding to a wavelengthabsorbed by sodium, and a second light source embedded within the secondcavity at a second position; wherein: the second light source isoperable to emit a second light into the body at a second wavelength oflight corresponding to a wavelength absorbed by potassium; an opticalsensor embedded within the third cavity at a third position, wherein theoptical sensor is to detect a portion of the first light and the secondlight reflected by a muscular-walled tube of the body at a depth belowan exterior of the body of the user; and a processing device is to:determine a sodium to potassium ratio of the user based on the reflectedfirst light and the reflected second light; and determine a hydrationcondition of the user based a trend of the sodium to potassium ratioover a period of time.
 2. The electrical device of claim 1, furthercomprising: a sensor interface, coupled to the optical sensor, whereinthe sensor interface is to: receive, from the optical sensor, theportion of first light and the second light reflected from themuscular-walled tube; take a first measurement of backscatter of thefirst wavelength of light using the detected portion of the first light;and take a second measurement of backscatter of the second wavelength oflight using the detected portion of the second light.
 3. The electricaldevice of claim 2, further wherein the processing device is further to:compare the first measurement of backscatter of the first wavelength oflight to a previous measurement of backscatter of the first wavelengthof light; determine a change in a sodium level of the body when anamount of backscatter of the first wavelength of light changes; comparethe second measurement of backscatter of the second wavelength of lightto a previous measurement of backscatter of the second wavelength oflight; and determine a change in a potassium level of the user when anamount of backscatter of the second wavelength of light changes.
 4. Theelectrical device of claim 3, wherein the processing device is furtherto determine that the hydration condition of the user is in a dehydratedcondition when the sodium level decreases.
 5. The electrical device ofclaim 3, wherein the processing device is further to determine that thehydration condition of the user is in a dehydrated when the potassiumlevel exceeds the sodium level.
 6. The electrical device of claim 1,wherein the first wavelength of light is between 535 nanometers and 735nanometers and wherein the second wavelength of light is between 680nanometers and 880 nanometers.
 7. An apparatus comprising: a housing; alight source disposed at an edge of the housing in a first position,wherein the light source, when affixed to a surface of a body, isoperable to emit light into the body from the first position; a firstoptical sensor disposed at the edge of the housing in a second position,the second position being a first fixed distance from the first positionto measure a first backscatter of the light from an artery of the bodyat a first depth below the surface of the body; and a second opticalsensor disposed at the edge of the housing in a third position, thethird position being a second fixed distance from the first position tomeasure a second backscatter of the light from a vein of the body at asecond depth below the surface of the body a processing deviceconfigured to determine a trend in a hydration condition of the bodybased on the first backscatter of light and the second backscatter oflight.
 8. The apparatus of claim 7, wherein the housing comprising acavity disposed on a first plane of an outer surface of the housing,wherein the light source is embedded within the cavity such that a firstend of the light source does not extend beyond the first plane of theouter surface of the housing.
 9. The apparatus of claim 8, wherein thelight source is embedded within the cavity such that the first end ofthe light source is flush with the first plane.
 10. The apparatus ofclaim 9 wherein the light source emits light of a first wavelengthbetween 535 nanometers and 735 nanometers and a second wavelengthbetween 680 nanometers and 880 nanometers.
 11. The apparatus of claim10, wherein the first wavelength corresponds to a measurement of sodiumin the body between 535 nanometers (nm) and 735 nm.
 12. The apparatus ofclaim 10, wherein the second wavelength corresponds to a measurement ofpotassium in the body between 680 nanometers (nm) and 880 nm.
 13. Theapparatus of claim 7, wherein the processing device is furtherconfigured to: determine a sodium to potassium ratio of the body basedon the first backscatter of light and the second backscatter of light;and determine the hydration condition of the body based on a trend ofthe sodium to potassium ratio.
 14. A method comprising: emitting, by alight source affixed to a body at a first position, a first wavelengthof light into the body; receiving, by an optical sensor affixed to thebody at a second position, light from a depth below a of the bodycorresponding to a muscular-walled tube of the body, wherein: the firstposition is at a fixed distance from the second position to detectbackscatter from the depth below the surface of the body; and the firstposition of the light source is at a first side of the muscular walledtube of the body and the second position of the optical sensor is at asecond side of the muscular walled tube such that the light source andthe optical sensor straddle the muscular walled tube; determining, by asensor interface, a current sodium to potassium ratio of the body basedon the detected backscatter of the first wavelength of light; comparing,by a processing device, the current sodium to potassium ratio to aprevious sodium to potassium ratio of the body; and determining ahydration condition of the body when the current sodium to potassiumratio is different than the previous sodium to potassium ratio.
 15. Themethod of claim 14, further comprising: determining the hydrationcondition of the body is a dehydration condition when the detectedbackscatter decreases; determining the hydration condition of the bodyis a hydrated condition when the detected backscatter increases; anddetermining the hydration condition of the body is a stable when thedetected backscatter is unchanged.
 16. The method of claim 14, whereinthe first wavelength of light is between 535 nanometers and 735nanometers and corresponds to a measurement of sodium in the body. 17.The method of claim 14, wherein the first wavelength of light is between680 nanometers and 880 nanometers and corresponds to a measurement ofpotassium in the body.
 18. The method of claim 14, wherein the firstwavelength of light is between 400 nanometers (nm) and 1800 nm.
 19. Themethod of claim 14, further comprising determining the hydrationcondition based on a trend of the sodium to potassium ratio over time.20. The method of claim 14, further comprising determining a trend inthe hydration condition of the body based on the trend of the sodium topotassium ratio.